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Traffic Injury Prevention Jun 2024Injury outcomes for powered two- and three-wheeler (PTW) riders are influenced by the rider posture. To enable analysis of PTW rider accidents and development of...
OBJECTIVE
Injury outcomes for powered two- and three-wheeler (PTW) riders are influenced by the rider posture. To enable analysis of PTW rider accidents and development of protection systems, detailed whole-body posture data is needed. Therefore, the aim of this study is to fill this gap by providing collections of average male whole-body postures, including subpopulation variability, for different PTW types. This will enable future studies to explore the influence of PTW rider posture variation and to support safety system development.
METHODS
3D photometric measurements of 51 anatomical landmarks were recorded on 20 (50th percentile male) volunteers in their preferred riding postures across three PTW types (naked, scooter, and touring). Following an outlier removal process, a principal component analysis (PCA) was performed to calculate average postures and principal components (PCs), to describe the observed posture variation, for each PTW. The visualization of the PCs was facilitated through kinematic linkage representations, connecting anatomical landmarks and estimated joint centers to form segments and characteristic joint angles.
RESULTS
The first seven PCs explained 80% of the variance in posture for each of the three PTWs. Across PTWs, these PCs frequently described combinations of postural features including variation in fore-aft seat positions, pelvic tilt, spinal curvature, head position, and extremity flexion-extension. Analysis revealed distinct differences in average postures across the three PTWs, on average, 10 ± 9° for the characteristic joint angles within a min-to-max range between the three PTWs. However, for all three PTWs, the variability between volunteers in characteristic joint angles on the same PTW were on average more than twice as large within a ± 2 SD range (26 ± 11°).
CONCLUSIONS
The results suggest that PTW rider posture variation must be addressed by involving simultaneous adjustments of multiple body parts, as described by each of the first seven PCs, as a direct consequence of the human body interconnectedness. Furthermore, the study's findings challenge conventional assumptions that the relative distance between PTWs' handlebar, seat, and foot support predominantly influences rider postures. Instead, the research demonstrates that individual variability has a substantial influence on rider posture and should be considered in PTW safety development.
PubMed: 38900933
DOI: 10.1080/15389588.2024.2351607 -
Pediatric Blood & Cancer Jun 2024Adolescent venous thromboembolism (VTE) has unique challenges in management, complications, and compliance to anticoagulants. Direct oral anticoagulants (DOACs) have... (Review)
Review
Adolescent venous thromboembolism (VTE) has unique challenges in management, complications, and compliance to anticoagulants. Direct oral anticoagulants (DOACs) have been approved for pediatric VTE management, with an increasing use especially in adolescents. Primary objective is to evaluate the safety and efficacy of DOAC therapy in adolescent VTE. Secondary objectives include adverse events, bleeding events, and overall mortality. A SR protocol was registered in PROSPERO 2022 (CRD42022363928). Databases were searched from inception to September 22, 2022. Studies with children aged 10-18 years, VTE diagnosis, DOAC therapy, randomized control trials (RCTs), cohort, and relevant study types were included. Studies including prophylaxis, non-DOAC therapy, arterial thrombosis, age outliers, non-relevant study types were excluded. Findings are reported in accordance to PRISMA 2020. Nine reports from five studies, published between 2016 and 2022, were included. Rivaroxaban was the most common DOAC. VTE recurrence was 0.02% in the rivaroxaban phase III trial and one patient in the dabigatran phase IIb/III trial. Complete/partial thrombus resolution (CR/PR) was 76.6% in the rivaroxaban phase III trial, and 83.9% in the dabigatran phase IIb/III trial. CR/PR was found to be 68.4% in Dhaliwal et al. study and 83.3% in Hassan et al. study. Major bleeding occurred in one patient. Headache and gastrointestinal symptoms were commonly seen. All-cause mortality occurred in a patient due to cancer progression. DOAC therapy in adolescent VTE had CR/PR in two-thirds of the patients, with low incidence of VTE recurrence and major bleeding. As there are only two randomized controlled trial (RCTs), future adolescents' studies are required to validate our results.
PubMed: 38899913
DOI: 10.1002/pbc.31131 -
Statistics in Medicine Jun 2024Meta-analysis is an essential tool to comprehensively synthesize and quantitatively evaluate results of multiple clinical studies in evidence-based medicine. In many...
Meta-analysis is an essential tool to comprehensively synthesize and quantitatively evaluate results of multiple clinical studies in evidence-based medicine. In many meta-analyses, the characteristics of some studies might markedly differ from those of the others, and these outlying studies can generate biases and potentially yield misleading results. In this article, we provide effective robust statistical inference methods using generalized likelihoods based on the density power divergence. The robust inference methods are designed to adjust the influences of outliers through the use of modified estimating equations based on a robust criterion, even when multiple and serious influential outliers are present. We provide the robust estimators, statistical tests, and confidence intervals via the generalized likelihoods for the fixed-effect and random-effects models of meta-analysis. We also assess the contribution rates of individual studies to the robust overall estimators that indicate how the influences of outlying studies are adjusted. Through simulations and applications to two recently published systematic reviews, we demonstrate that the overall conclusions and interpretations of meta-analyses can be markedly changed if the robust inference methods are applied and that only the conventional inference methods might produce misleading evidence. These methods would be recommended to be used at least as a sensitivity analysis method in the practice of meta-analysis. We have also developed an R package, robustmeta, that implements the robust inference methods.
PubMed: 38899515
DOI: 10.1002/sim.10157 -
Computers in Biology and Medicine Jun 2024The Instantaneous Signal Loss Simulation (InSiL) model is a promising alternative to the classical mono-exponential fitting of the Modified Look-Locker...
The Instantaneous Signal Loss Simulation (InSiL) model is a promising alternative to the classical mono-exponential fitting of the Modified Look-Locker Inversion-recovery (MOLLI) sequence in cardiac T mapping applications, which achieves better accuracy and is less sensitive to heart rate (HR) variations. Classical non-linear least squares (NLLS) estimation methods require some parameters of the model to be fixed a priori in order to give reliable T estimations and avoid outliers. This introduces further bias in the estimation, reducing the advantages provided by the InSiL model. In this paper, a novel Bayesian estimation method using a hierarchical model is proposed to fit the parameters of the InSiL model. The hierarchical Bayesian modeling has a shrinkage effect that works as a regularizer for the estimated values, by pulling spurious estimated values toward the group-mean, hence reducing greatly the number of outliers. Simulations, physical phantoms, and in-vivo human cardiac data have been used to show that this approach estimates accurately all the InSiL parameters, and achieve high precision estimation of the T compared to the classical MOLLI model and NLLS InSiL estimation.
PubMed: 38897148
DOI: 10.1016/j.compbiomed.2024.108753 -
Planta Jun 2024By studying Cistus albidus shrubs in their natural habitat, we show that biological outliers can help us to understand the causes and consequences of maximum...
By studying Cistus albidus shrubs in their natural habitat, we show that biological outliers can help us to understand the causes and consequences of maximum photochemical efficiency decreases in plants, thus reinforcing the importance of integrating these often-neglected data into scientific practice. Outliers are individuals with exceptional traits that are often excluded of data analysis. However, this may result in very important mistakes not accurately capturing the true trajectory of the population, thereby limiting our understanding of a given biological process. Here, we studied the role of biological outliers in understanding the causes and consequences of maximum photochemical efficiency decreases in plants, using the semi-deciduous shrub C. albidus growing in a Mediterranean-type ecosystem. We assessed interindividual variability in winter, spring and summer maximum PSII photochemical efficiency in a population of C. albidus growing under Mediterranean conditions. A strong correlation was observed between maximum PSII photochemical efficiency (F/F ratio) and leaf water desiccation. While decreases in maximum PSII photochemical efficiency did not result in any damage at the organ level during winter, reductions in the F/F ratio were associated to leaf mortality during summer. However, all plants could recover after rainfalls, thus maximum PSII photochemical efficiency decreases did not result in an increased mortality at the organism level, despite extreme water deficit and temperatures exceeding 40ºC during the summer. We conclude that, once methodological outliers are excluded, not only biological outliers must not be excluded from data analysis, but focusing on them is crucial to understand the causes and consequences of maximum PSII photochemical efficiency decreases in plants.
Topics: Photosystem II Protein Complex; Seasons; Plant Leaves; Cistus; Photosynthesis; Ecosystem; Water; Temperature; Chlorophyll
PubMed: 38896307
DOI: 10.1007/s00425-024-04466-3 -
Journal of Chemical Information and... Jun 2024In drug discovery, the in silico prediction of binding affinity is one of the major means to prioritize compounds for synthesis. Alchemical relative binding free energy...
In drug discovery, the in silico prediction of binding affinity is one of the major means to prioritize compounds for synthesis. Alchemical relative binding free energy (RBFE) calculations based on molecular dynamics (MD) simulations are nowadays a popular approach for the accurate affinity ranking of compounds. MD simulations rely on empirical force field parameters, which strongly influence the accuracy of the predicted affinities. Here, we evaluate the ability of six different small-molecule force fields to predict experimental protein-ligand binding affinities in RBFE calculations on a set of 598 ligands and 22 protein targets. The public force fields OpenFF Parsley and Sage, GAFF, and CGenFF show comparable accuracy, while OPLS3e is significantly more accurate. However, a consensus approach using Sage, GAFF, and CGenFF leads to accuracy comparable to OPLS3e. While Parsley and Sage are performing comparably based on aggregated statistics across the whole dataset, there are differences in terms of outliers. Analysis of the force field reveals that improved parameters lead to significant improvement in the accuracy of affinity predictions on subsets of the dataset involving those parameters. Lower accuracy can not only be attributed to the force field parameters but is also dependent on input preparation and sampling convergence of the calculations. Especially large perturbations and nonconverged simulations lead to less accurate predictions. The input structures, Gromacs force field files, as well as the analysis Python notebooks are available on GitHub.
PubMed: 38895959
DOI: 10.1021/acs.jcim.4c00417 -
Skin Research and Technology : Official... Jun 2024Research has previously established connections between the intestinal microbiome and the progression of some cancers. However, there is a noticeable gap in the...
OBJECTIVE
Research has previously established connections between the intestinal microbiome and the progression of some cancers. However, there is a noticeable gap in the literature in regard to using Mendelian randomisation (MR) to delve into potential causal relationships between the gut microbiota (GM) and basal cell carcinoma (BCC). Therefore, the purpose of our study was to use MR to explore the causal relationship between four kinds of GM (Bacteroides, Streptococcus, Proteobacteria and Lachnospiraceae) and BCC.
METHODS
We used genome-wide association study (GWAS) data and MR to explore the causal relationship between four kinds of GM and BCC. This study primarily employed the random effect inverse variance weighted (IVW) model for analysis, as complemented by additional methods including the simple mode, weighted median, weighted mode and MR‒Egger methods. We used heterogeneity and horizontal multiplicity to judge the reliability of each analysis. MR-PRESSO was mainly used to detect and correct outliers.
RESULTS
The random-effects IVW results showed that Bacteroides (OR = 0.936, 95% CI = 0.787-1.113, p = 0.455), Streptococcus (OR = 0.974, 95% CI = 0.875-1.083, p = 0.629), Proteobacteria (OR = 1.113, 95% CI = 0.977-1.267, p = 0.106) and Lachnospiraceae (OR = 1.027, 95% CI = 0.899-1.173, p = 0.688) had no genetic causal relationship with BCC. All analyses revealed no horizontal pleiotropy, heterogeneity or outliers.
CONCLUSION
We found that Bacteroides, Streptococcus, Proteobacteria and Lachnospiraceae do not increase the incidence of BCC at the genetic level, which provides new insight for the study of GM and BCC.
Topics: Humans; Mendelian Randomization Analysis; Carcinoma, Basal Cell; Gastrointestinal Microbiome; Skin Neoplasms; Genome-Wide Association Study; Streptococcus; Proteobacteria; Bacteroides; Genetic Predisposition to Disease; Polymorphism, Single Nucleotide
PubMed: 38895789
DOI: 10.1111/srt.13804 -
Skin Research and Technology : Official... Jun 2024An increasing amount of research demonstrates that metabolic disorders are related to rosacea. However, the correlations and causal relationships among them remain...
BACKGROUND
An increasing amount of research demonstrates that metabolic disorders are related to rosacea. However, the correlations and causal relationships among them remain unknown.
METHODS
We conducted not only forward 2-sample MR (Mendelian randomization) analyses but also reverse MR analyses which showed positive results in the forward MR analysis. In the forward MR analyses, inverse-variance weighted (IVW) and MR-Egger were performed as MR analyses. Cochran's Q test and the MR-Egger Intercept were used for sensitivity analyses. Concerning reverse MR analyses, IVW, MR-Egger, weighted median, simple mode, and weighted mode were applied. Cochran's Q test, MR-Egger Intercept, and MR pleiotropy residual sum and outlier (MR-PRESSO) outlier test were applied as sensitivity analyses.
RESULTS
A total of 24 metabolites and 1 metabolite ratio were shown to have a causal effect on rosacea. N-lactoyl phenylalanine (N-Lac-Phe) was estimated as statistically significant by Bonferroni correction. Interestingly, we found three metabolites that were negatively associated with rosacea, especially caffeine, which are in line with the results of a large cohort study of females. For reverse MR analysis, we revealed that rosacea could potentially decrease the generation of two metabolites: octadecenedioate (C18:1-DC) and methyl vanillate sulfate.
CONCLUSION
This study identified blood metabolites that may be associated with the development of rosacea. However, the exact mechanism by which these positive metabolites influence rosacea remains uncertain due to the paucity of experimental investigations. The combination of genetics and metabolomics offers novel viewpoints on the research of underlying mechanisms of rosacea and has significant value in screening and prevention of rosacea.
Topics: Rosacea; Humans; Mendelian Randomization Analysis; Female; Causality
PubMed: 38895784
DOI: 10.1111/srt.13796 -
SAGE Open Medicine 2024Irregular menstrual cycle has negative health and psychosocial repercussions for women of reproductive age worldwide. However, there is no national data for policymakers... (Review)
Review
INTRODUCTION
Irregular menstrual cycle has negative health and psychosocial repercussions for women of reproductive age worldwide. However, there is no national data for policymakers and health planners in Ethiopia. Therefore, this review aimed to determine the overall burden of irregular menstrual cycle and predictors among reproductive-age women in Ethiopia.
METHODS
International databases (SCOPUS, CINAHL, CAB Abstract, EMBASE, PubMed, Web of Science, Google, and Google Scholar) and lists of references were employed to search literature in Ethiopia. The random-effects model was used to calculate the odds ratios of the outcome variable using STATA version 18. The heterogeneity of the studies was measured by computing and -values. In addition, sensitivity analysis and funnel plots were performed to test the stability of pooled data in the presence of outliers and publication bias.
RESULTS
The review includes 21 studies and 9109 populations. The overall burden of irregular menstrual cycles among reproductive-age women was 35% (95% CI: 30-41) with = 96.96%. Sleeping for <5 h a day (AOR: 2.49; 95% CI: 1.49-3.49) and a stressful life (AOR: 3.15; 95% CI: 1.44-4.85) were predictors of irregular menstrual cycles.
CONCLUSION
More than one in every three reproductive-age women in Ethiopia experience irregular menstrual cycles. Sleeping for <5 h a day and stress increase the likelihood of an irregular menstrual cycle, which can be modified by improving sleeping hours and decreasing stress stimulators through psychotherapy.
PubMed: 38895544
DOI: 10.1177/20503121241259623 -
BioRxiv : the Preprint Server For... Jun 2024Quality control (QC) is a crucial step to ensure the reliability and accuracy of the data obtained from RNA sequencing experiments, including spatially-resolved...
Quality control (QC) is a crucial step to ensure the reliability and accuracy of the data obtained from RNA sequencing experiments, including spatially-resolved transcriptomics (SRT). Existing QC approaches for SRT that have been adopted from single-nucleus RNA sequencing (snRNA-seq) methods are confounded by spatial biology and are inappropriate for SRT data. In addition, no methods currently exist for identifying histological tissue artifacts unique to SRT. Here, we introduce SpotSweeper, spatially-aware QC methods for identifying local outliers and regional artifacts in SRT. SpotSweeper evaluates the quality of individual spots relative to their local neighborhood, thus minimizing bias due to biological heterogeneity, and uses multiscale methods to detect regional artifacts. Using SpotSweeper on publicly available data, we identified a consistent set of Visium barcodes/spots as systematically low quality and demonstrate that SpotSweeper accurately identifies two distinct types of regional artifacts, resulting in improved downstream clustering and marker gene detection for spatial domains.
PubMed: 38895212
DOI: 10.1101/2024.06.06.597765