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PloS One 2024The underwater laser polarization detection technology integrates the polarization characteristics of light into the detection and identification of underwater targets....
The underwater laser polarization detection technology integrates the polarization characteristics of light into the detection and identification of underwater targets. Addressing the challenge of poor accuracy in identifying targets in strong underwater scattering environments, this article proposes an overall scheme for a laser polarization underwater detection device that suppresses scatter using polarized pulse signals. By overcoming key technological barriers in the design of polarization-preserving optical detection systems and utilizing the method of differential amplitude to measure polarization, a laser polarization underwater detection device was developed and underwater polarization detection experiments were conducted, achieving precise detection of underwater targets. The results indicate that the underwater detection device we designed has a root mean square error of less than 5.7% to detect the polarization of the target, demonstrating the accuracy and precision of the underwater detection device.
Topics: Lasers; Scattering, Radiation; Water; Light
PubMed: 38917184
DOI: 10.1371/journal.pone.0305929 -
PloS One 2024This observational study aimed to evaluate the intra- and inter-operator reliability of a digital palpation device in measuring compressive stiffness of the patellar... (Observational Study)
Observational Study
This observational study aimed to evaluate the intra- and inter-operator reliability of a digital palpation device in measuring compressive stiffness of the patellar tendon at different knee angles in talent and elite volleyball players. Second aim was to examine differences in reliability when measuring at different knee angles, between dominant and non-dominant knees, between sexes, and with age. Two operators measured stiffness at the midpoint of the patellar tendon in 45 Dutch volleyball players at 0°, 45° and 90° knee flexion, on both the dominant and non-dominant side. We found excellent intra-operator reliability (ICC>0.979). For inter-operator reliability, significant differences were found in stiffness measured between operators (p<0.007). The coefficient of variance significantly decreased with increasing knee flexion (2.27% at 0°, 1.65% at 45° and 1.20% at 90°, p<0.001). In conclusion, the device appeared to be reliable when measuring compressive stiffness of the patellar tendon in elite volleyball players, especially at 90° knee flexion. Inter-operator reliability appeared to be questionable. More standardized positioning and measurement protocols seem necessary.
Topics: Humans; Volleyball; Male; Female; Patellar Ligament; Palpation; Reproducibility of Results; Young Adult; Adult; Range of Motion, Articular; Knee Joint; Adolescent; Biomechanical Phenomena; Observer Variation
PubMed: 38917106
DOI: 10.1371/journal.pone.0304743 -
Microbiology Spectrum Jun 2024Sonicating explanted prosthetic implants to physically remove biofilms is a recognized method for improving the microbiological diagnosis of prosthetic joint infection...
UNLABELLED
Sonicating explanted prosthetic implants to physically remove biofilms is a recognized method for improving the microbiological diagnosis of prosthetic joint infection (PJI); however, chemical and enzymatic treatments have been investigated as alternative biofilm removal methods. We compared the biofilm dislodging efficacy of sonication followed by the addition of enzyme cocktails with different activity spectra in the diagnosis of PJI with that of the sonication of fluid cultures alone. Consecutive patients who underwent prosthesis explantation due to infection at our institution were prospectively enrolled for 1 year. The diagnostic procedure included the collection of five intraoperative tissue cultures, sonication of the removed devices, and conventional culture of the sonication fluid. The resulting sonication fluid was also treated with an enzyme cocktail consisting of homemade dispersin B (0.04 µg/mL) and proteinase K (Sigma; 100 µg/mL) for 45 minutes at 37°C. The resulting sonication (S) and sonication with subsequent enzymatic treatment (SE) fluids were plated for aerobic and anaerobic culture broth for 7 days (aerobic) or 14 days (anaerobic). Identification was performed by matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (Bruker). We included 107 patients from whom a prosthetic implant had been removed, among which PJI was diagnosed in 36 (34%). The sensitivity of S alone was significantly greater than that of SE alone (82% vs 71%; < 0.05). Four patients with PJI were positive after sonication alone but negative after sonication plus enzymatic treatment. The four microorganisms missed after the addition of the enzyme cocktail were , two coagulase-negative and . In conclusion, sonication alone was more sensitive than sonication followed by enzymatic treatment. The combination of these two methods had no synergistic effect; in contrast, the results suggest that the combination of both dislodgment methods affects the viability of gram-positive microorganisms.
IMPORTANCE
While the potential of sonication and enzymes as biofilm dispersal agents has been previously described, the originality of our work resides in the combination of both methods, which is hypothesized to enhance the ability to remove biofilm and, therefore, improve the microbiological diagnosis of PJI.
PubMed: 38916322
DOI: 10.1128/spectrum.00020-24 -
Reumatismo Jun 2024To evaluate the association of the rs11125908 polymorphism in the COMMD1 gene in the Cuban population with rheumatoid arthritis (RA).
OBJECTIVE
To evaluate the association of the rs11125908 polymorphism in the COMMD1 gene in the Cuban population with rheumatoid arthritis (RA).
METHODS
In this case-control study, 161 RA patients and 150 control subjects were genotyped for rs11125908 by the allele-specific polymerase chain reaction method. DNA sequencing was used to verify the assignation of the polymorphism. The odds ratios (OR) and their 95% confidence interval were calculated by logistic regression to determine the associations between genotypes and RA using the SNPStats software.
RESULTS
An association of the single nucleotide polymorphism with the disease was found in the overdominant model (p=0.025; OR=1.91) for the AG genotype. Our analyses revealed an association between rs11125908 and the subgroup of patients with swollen joints < median under the codominant model for AG (p=0.034; OR=2.30) and GG genotype (p=0.034; OR=0.82) and with the overdominant model (p=0.01; OR=2.38). The subgroup of patients with an age of onset lower than the mean and AG genotype showed an association in the overdominant model (p=0.027; OR=2.27). Disease activity score 28 with erythrocyte sedimentation rate and disease duration variables were not associated with the rs11125908 polymorphism.
CONCLUSIONS
rs11125908 was associated with RA and with the number of swollen joints and age of onset subgroup analyses. We provide concepts for treatments for RA, based on pharmacological management of COMMD1 expression.
Topics: Humans; Arthritis, Rheumatoid; Polymorphism, Single Nucleotide; Male; Female; Case-Control Studies; Middle Aged; Cuba; Adult; Adaptor Proteins, Signal Transducing; Genotype; Genetic Predisposition to Disease; Aged
PubMed: 38916163
DOI: 10.4081/reumatismo.2024.1691 -
Frontiers in Plant Science 2024Genomic prediction has mostly been used in single environment contexts, largely ignoring genotype x environment interaction, which greatly affects the performance of...
Genomic prediction has mostly been used in single environment contexts, largely ignoring genotype x environment interaction, which greatly affects the performance of plants. However, in the last decade, prediction models including marker x environment (MxE) interaction have been developed. We evaluated the potential of genomic prediction in red clover ( L.) using field trial data from five European locations, obtained in the Horizon 2020 EUCLEG project. Three models were compared: (1) single environment (SingleEnv), (2) across environment (AcrossEnv), (3) marker x environment interaction (MxE). Annual dry matter yield (DMY) gave the highest predictive ability (PA). Joint analyses of DMY from years 1 and 2 from each location varied from 0.87 in Britain and Switzerland in year 1, to 0.40 in Serbia in year 2. Overall, crude protein (CP) was predicted poorly. PAs for date of flowering (DOF), however ranged from 0.87 to 0.67 for Britain and Switzerland, respectively. Across the three traits, the MxE model performed best and the AcrossEnv worst, demonstrating that including marker x environment effects can improve genomic prediction in red clover. Leaving out accessions from specific regions or from specific breeders' material in the cross validation tended to reduce PA, but the magnitude of reduction depended on trait, region and breeders' material, indicating that population structure contributed to the high PAs observed for DMY and DOF. Testing the genomic estimated breeding values on new phenotypic data from Sweden showed that DMY training data from Britain gave high PAs in both years (0.43-0.76), while DMY training data from Switzerland gave high PAs only for year 1 (0.70-0.87). The genomic predictions we report here underline the potential benefits of incorporating MxE interaction in multi-environment trials and could have perspectives for identifying markers with effects that are stable across environments, and markers with environment-specific effects.
PubMed: 38916032
DOI: 10.3389/fpls.2024.1407609 -
Frontiers in Neurology 2024Evaluate safety and effectiveness of thermal radiofrequency in the musculocutaneous nerve in patients with focal elbow flexor spasticity.
OBJECTIVE
Evaluate safety and effectiveness of thermal radiofrequency in the musculocutaneous nerve in patients with focal elbow flexor spasticity.
DESIGN
Ambispective observational follow-up study. Patients with focal spasticity secondary to central nervous system injury with elbow flexor pattern who received thermal radiofrequency treatment in the musculocutaneous nerve between 2021 and 2023 were included.
SUBJECTS
12 patients.
METHODS
Ultrasound-guided thermal radiofrequency was applied to the musculocutaneous nerve at 80°C for 90 s. Effectiveness was assessed prior to thermal radiofrequency and at 6 months using scales to measure pain (VAS), spasticity (MAS), disability (DAS), quality of life (SQol-6D), patient-perceived and physician-perceived satisfaction (PIG-C, PGA), and goal attainment (GAS). Elbow joint range of motion was evaluated via goniometry. Safety was evaluated by assessing side effects.
RESULTS
Patients had statistically significant improvements in spasticity ( = 0.003), severe elbow flexion ( = 0.02), pain ( = 0.046), functioning ( < 0.05), and spasticity-related quality of life ( < 0.05 in three sections). Furthermore, treatment goals were attained. Patient- and physician-perceived clinical improvement was achieved. Regarding side effects, two patients had dysesthesia that was self-limiting, with maximum duration of 1 month.
CONCLUSION
Thermal radiofrequency in the musculocutaneous nerve can be a safe, effective treatment for patients with severe spasticity with an elbow flexor pattern.
PubMed: 38915804
DOI: 10.3389/fneur.2024.1369947 -
BioRxiv : the Preprint Server For... Jun 2024Cartilage plays a crucial role in skeletal development and function, and abnormal development contributes to genetic and age-related skeletal disease. To better...
UNLABELLED
Cartilage plays a crucial role in skeletal development and function, and abnormal development contributes to genetic and age-related skeletal disease. To better understand how human cartilage develops , we jointly profiled the transcriptome and open chromatin regions in individual nuclei recovered from distal femurs at 2 fetal timepoints. We used these multiomic data to identify transcription factors expressed in distinct chondrocyte subtypes, link accessible regulatory elements with gene expression, and predict transcription factor-based regulatory networks that are important for growth plate or epiphyseal chondrocyte differentiation. We developed a human pluripotent stem cell platform for interrogating the function of predicted transcription factors during chondrocyte differentiation and used it to test . We expect new regulatory networks we uncovered using multiomic data to be important for promoting cartilage health and treating disease, and our platform to be a useful tool for studying cartilage development .
STATEMENT OF SIGNIFICANCE
The identity and integrity of the articular cartilage lining our joints are crucial to pain-free activities of daily living. Here we identified a gene regulatory landscape of human chondrogenesis at single cell resolution, which is expected to open new avenues of research aimed at mitigating cartilage diseases that affect hundreds of millions of individuals world-wide.
PubMed: 38915712
DOI: 10.1101/2024.06.12.598666 -
BioRxiv : the Preprint Server For... Jun 2024With the increased reliance on multi-omics data for bulk and single cell analyses, the availability of robust approaches to perform unsupervised analysis for clustering,...
MOTIVATION
With the increased reliance on multi-omics data for bulk and single cell analyses, the availability of robust approaches to perform unsupervised analysis for clustering, visualization, and feature selection is imperative. Joint dimensionality reduction methods can be applied to multi-omics datasets to derive a global sample embedding analogous to single-omic techniques such as Principal Components Analysis (PCA). Multiple co-inertia analysis (MCIA) is a method for joint dimensionality reduction that maximizes the covariance between block- and global-level embeddings. Current implementations for MCIA are not optimized for large datasets such such as those arising from single cell studies, and lack capabilities with respect to embedding new data.
RESULTS
We introduce nipalsMCIA , an MCIA implementation that solves the objective function using an extension to Non-linear Iterative Partial Least Squares (NIPALS), and shows significant speed-up over earlier implementations that rely on eigendecompositions for single cell multi-omics data. It also removes the dependence on an eigendecomposition for calculating the variance explained, and allows users to perform out-of-sample embedding for new data. nipalsMCIA provides users with a variety of pre-processing and parameter options, as well as ease of functionality for down-stream analysis of single-omic and global-embedding factors.
AVAILABILITY
nipalsMCIA is available as a BioConductor package at https://bioconductor.org/packages/release/bioc/html/nipalsMCIA.html , and includes detailed documentation and application vignettes. Supplementary Materials are available online.
PubMed: 38915554
DOI: 10.1101/2024.06.07.597819 -
Frontiers in Immunology 2024Rheumatoid arthritis (RA) is an autoimmune disease causing progressive joint damage. Early diagnosis and treatment is critical, but remains challenging due to RA... (Review)
Review
Rheumatoid arthritis (RA) is an autoimmune disease causing progressive joint damage. Early diagnosis and treatment is critical, but remains challenging due to RA complexity and heterogeneity. Machine learning (ML) techniques may enhance RA management by identifying patterns within multidimensional biomedical data to improve classification, diagnosis, and treatment predictions. In this review, we summarize the applications of ML for RA management. Emerging studies or applications have developed diagnostic and predictive models for RA that utilize a variety of data modalities, including electronic health records, imaging, and multi-omics data. High-performance supervised learning models have demonstrated an Area Under the Curve (AUC) exceeding 0.85, which is used for identifying RA patients and predicting treatment responses. Unsupervised learning has revealed potential RA subtypes. Ongoing research is integrating multimodal data with deep learning to further improve performance. However, key challenges remain regarding model overfitting, generalizability, validation in clinical settings, and interpretability. Small sample sizes and lack of diverse population testing risks overestimating model performance. Prospective studies evaluating real-world clinical utility are lacking. Enhancing model interpretability is critical for clinician acceptance. In summary, while ML shows promise for transforming RA management through earlier diagnosis and optimized treatment, larger scale multisite data, prospective clinical validation of interpretable models, and testing across diverse populations is still needed. As these gaps are addressed, ML may pave the way towards precision medicine in RA.
Topics: Arthritis, Rheumatoid; Humans; Precision Medicine; Machine Learning; Rheumatology; Disease Management
PubMed: 38915408
DOI: 10.3389/fimmu.2024.1409555 -
Frontiers in Robotics and AI 2024This paper introduces DAC-HRC, a novel cognitive architecture designed to optimize human-robot collaboration (HRC) in industrial settings, particularly within the...
This paper introduces DAC-HRC, a novel cognitive architecture designed to optimize human-robot collaboration (HRC) in industrial settings, particularly within the context of Industry 4.0. The architecture is grounded in the Distributed Adaptive Control theory and the principles of joint intentionality and interdependence, which are key to effective HRC. Joint intentionality refers to the shared goals and mutual understanding between a human and a robot, while interdependence emphasizes the reliance on each other's capabilities to complete tasks. DAC-HRC is applied to a hybrid recycling plant for the disassembly and recycling of Waste Electrical and Electronic Equipment (WEEE) devices. The architecture incorporates several cognitive modules operating at different timescales and abstraction levels, fostering adaptive collaboration that is personalized to each human user. The effectiveness of DAC-HRC is demonstrated through several pilot studies, showcasing functionalities such as turn-taking interaction, personalized error-handling mechanisms, adaptive safety measures, and gesture-based communication. These features enhance human-robot collaboration in the recycling plant by promoting real-time robot adaptation to human needs and preferences. The DAC-HRC architecture aims to contribute to the development of a new HRC paradigm by paving the way for more seamless and efficient collaboration in Industry 4.0 by relying on socially adept cognitive architectures.
PubMed: 38915371
DOI: 10.3389/frobt.2024.1248646