Associations between gut microbiota and adverse neurodevelopmental outcomes in preterm infants: a two-sample Mendelian randomization study

Gut microbiota are associated with adverse neurodevelopmental outcomes in preterm infants; however, the precise causal relationship remains unclear. In this study, we conducted a two-sample Mendelian randomization (MR) analysis to comprehensively study the relationship between gut microbiota and adverse neurodevelopmental outcomes in preterm infants and identify specific causal bacteria that may be associated with the occurrence and development of adverse neurodevelopmental outcomes in preterm infants. The genome-wide association analysis (GWAS) of the MiBioGen biogroup was used as the exposure data. The GWAS of six common adverse neurodevelopmental outcomes in premature infants from the FinnGen consortium R9 was used as the outcome data. Genetic variations, namely, single nucleotide polymorphisms (SNPs) below the locus-wide significance level (1 × 10−5) and genome-wide statistical significance threshold (5 × 10−8) were selected as instrumental variables (IVs). MR studies use inverse variance weighting (IVW) as the main method. To supplement this, we also applied three additional MR methods: MR-Egger, weighted median, and weighted mode. In addition, the Cochrane’s Q test, MR-Egger intercept test, Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO), and leave-one-out methods were used for sensitivity analysis. Our study shows a causal relationship between specific gut microbiota and neurodevelopmental outcomes in preterm infants. These findings provide new insights into the mechanism by which gut microbiota may mediate adverse neurodevelopmental outcomes in preterm infants

New findings on CD16brightCD62Ldim neutrophil subtypes in sepsis-associated ARDS: an observational clinical study

BackgroundThe CD16brightCD62Ldim neutrophil subtype is a recently identified neutrophil subtype. The aim of this study was to evaluate changes of peripheral blood CD16brightCD62Ldim neutrophils in patients with sepsis-associated ARDS.MethodsWe prospectively recruited adult patients with sepsis-associated ARDS in the intensive care unit (ICU). Patient demographic data, medical history information, and laboratory data were collected within 48 hours of enrollment, and flow cytometry was applied to analyze the CD16brightCD62Ldim neutrophil subtype in the patients’ peripheral blood. Multifactor COX regression models were used to analyze factors affecting prognosis, and Spearman correlation coefficients were used to analyze clinical and laboratory indicators affecting complications of infection.ResultsOf the 40 patients, 9 patients died by the 28-day follow-up, indicating a mortality rate of 22.5%. Patients in the nonsurvival group had higher CD16brightCD62Ldim neutrophil levels. Patients with sepsis-associated ARDS who had a baseline proportion of CD16brightCD62Ldim neutrophil subtypes to total neutrophils in peripheral blood >3.73% had significantly higher 28-day mortality, while patients with CD16brightCD62Ldim neutrophil subtypes counts >2.62×109/L were also associated with significantly higher 28-day mortality. The percentage of the CD16brightCD62Ldim neutrophil subtype (HR=5.305, 95% CI 1.986-14.165, p=0.001) and IL-8 (HR=3.852, 95% CI 1.561-9.508, p=0.003) were independent risk factors for the development of infectious complications in patients with sepsis-related ARDS. The percentage of CD16brightCD62Ldim neutrophil subtypes predicted an AUC of 0.806 (95% CI 0.147-0.964, P=0.003) for the development of infectious complications, and 0.742 (95% CI 0.589-0.895, P=0.029) for the prediction of death within 28 days.ConclusionWe identified for the first time that CD16brightCD62Ldim neutrophils are elevated in patients with sepsis-associated ARDS and are associated with infectious complications and poor prognosis. The percentage of CD16brightCD62Ldim neutrophil subtypes may serve as a predictor of the development of infectious complications in patients with ARDS

Method of 3D Coating Accumulation Modeling Based on Inclined Spraying

In the process of repairing the surface of products in aviation, aerospace, and other fields by spraying, accurate 3D cumulative-coating modeling is an important research issue in spraying-process simulation. The approach to this issue is a 3D cumulative-coating model based on inclined spraying. Firstly, an oblique spraying layer cumulative model was established, which could quickly collect the coating thickness distribution data of different spray distances. Secondly, 3D cumulative-coating modeling was conducted with the distance between the measuring point and the axis of the spray gun and the spraying distance between the measuring points as the input parameters, and the coating thickness of the measuring point as the output parameter. The experimental results show that the mean relative error of the cumulative model of the oblique spraying layer is less than 4.1% in the case of a 170~290 mm spraying distance and that the model is applicable in the range of −80~80 mm, indicating that the data on the oblique spraying coating proposed in this paper is accurate and fast. The accuracy of the 3D cumulative-coating model proposed in this paper is 1.2% and 21.5% higher than that of the two similar models, respectively. Therefore, the approach of 3D cumulative-coating modeling based on inclined distance spraying is discovered, demonstrating the advantages of fast and accurate modeling and enabling accurate 3D cumulative-coating modeling for spraying process simulation

Variable Structure Control and Its Ground Experimental Test for the Space Station Robot

Building a simulated weightless test system on the ground while making comprehensive comparisons of design controllers for a large and heavy multijointed space station robot is not an easy task. To save cost and improve the efficiency of the test, this paper develops a plan in which controllers undergo preliminary testing in a 6-DOF industrial robot. The key idea is gravity compensation included within the dynamic control algorithm of the robot to replace the function of the microgravity environment. It is generally difficult to build an accurate dynamic model for a serial-joint robot in a practical manner. Therefore, to guarantee the stability of the 6-DOF industrial robot in which the dynamic model is built inaccurately, we propose one of the simplest variable structure (VS) controllers, and the stability of the system is analyzed through the Lyapunov method. Last, experiments are carried out to provide preliminary comparisons among three potential algorithms for the space robot in a low-cost and efficient approach

The first chromosomal-level genome assembly and annotation of white suckerfish Remora albescens

Abstract Remora albescens, also known as white suckerfish, recognized for its distinctive suction-cup attachment behavior and medicinal significance. In this study, we produced a high-quality chromosome-level genome assembly of R. albescens through the integration of 23.87 Gb PacBio long reads, 64.54 Gb T7 short reads, and 88.63 Gb Hi-C data. Initially, we constructed a contig-level genome assembly totaling 605.30 Mb with a contig N50 of 23.12 Mb. Subsequently, employing Hi-C technology, approximately 99.68% (603.38 Mb) of the contig-level genome was successfully assigned to 23 pseudo-chromosomes. Through the integration of homologous-based predictions, ab initio predictions, and RNA-sequencing methods, we successfully identified a comprehensive set of 22,445 protein-coding genes. Notably, 96.36% (21,629 genes) of these were effectively annotated with functional information. The genome assembly achieved an estimated completeness of 98.1% according to BUSCO analysis. This work promotes the applicability of the R. albescens genome, laying a solid foundation for future investigations into genomics, biology, and medicinal importance within this species

Enhancing SCR activity and anti-poisoning of MnOx/m-ZrO2 catalysts by metal doping

This study investigated the impact of metal doping on the DeNOx and anti-poisoning performance of MnOx/m-ZrO2. The DeNOx performance increases from 96% to nearly 100% by Co or Sm doping. However, the anti-poisoning performance was enhanced more by Sm doping, and the DeNOx performance remained at 90.97% after water and sulfur compound poisoning. The improved redox performance caused by the interaction between Sm and Mn resulted in more acidic sites that aid in the adsorption of NOx and NH3, and the presence of Sm effectively inhibits the formation of sulfate and ammonium sulfate, thus enhancing the DeNOx and anti-poisoning performance

A novel 2D/3D hierarchical registration framework via principal-directional Fourier transform operator

An effective registration framework between preoperative 3D computed tomography and intraoperative 2D x-ray images is crucial in image-guided therapy. In this paper, a novel 2D/3D hierarchical registration framework via principal-directional Fourier transform operator (HRF-PDFTO) is proposed. First, a PDFTO was established to obtain the in-plane translation and rotation invariance. Then, an initial free template-matching approach based on PDFTO was utilized to avoid initial value assignment and expand the capture range of registration. Finally, the hierarchical registration framework, HRF-PDFTO, was proposed to reduce the dimensions of the registration search space from n(6) to n(2). The experimental results demonstrated that the proposed HRF-PDFTO has good performance with an accuracy of 0.72 mm, and a single registration time of 16 s, which improves the registration efficiency by ten times. Consequently, the HRF-PDFTO can meet the accuracy and efficiency requirements of 2D/3D registration in related clinical applications

Experimental validation and comprehensive analysis of m6A methylation regulators in intervertebral disc degeneration subpopulation classification

Abstract Intervertebral disc degeneration (IVDD) is one of the most prevalent causes of chronic low back pain. The role of m6A methylation modification in disc degeneration (IVDD) remains unclear. We investigated immune-related m6A methylation regulators as IVDD biomarkers through comprehensive analysis and experimental validation of m6A methylation regulators in disc degeneration. The training dataset was downloaded from the GEO database and analysed for differentially expressed m6A methylation regulators and immunological features, the differentially regulators were subsequently validated by a rat IVDD model and RT-qPCR. Further screening of key m6A methylation regulators based on machine learning and LASSO regression analysis. Thereafter, a predictive model based on key m6A methylation regulators was constructed for training sets, which was validated by validation set. IVDD patients were then clustered based on the expression of key m6A regulators, and the expression of key m6A regulators and immune infiltrates between clusters was investigated to determine immune markers in IVDD. Finally, we investigated the potential role of the immune marker in IVDD through enrichment analysis, protein-to-protein network analysis, and molecular prediction. By analysising of the training set, we revealed significant differences in gene expression of five methylation regulators including RBM15, YTHDC1, YTHDF3, HNRNPA2B1 and ALKBH5, while finding characteristic immune infiltration of differentially expressed genes, the result was validated by PCR. We then screen the differential m6A regulators in the training set and identified RBM15 and YTHDC1 as key m6A regulators. We then used RBM15 and YTHDC1 to construct a predictive model for IVDD and successfully validated it in the training set. Next, we clustered IVDD patients based on the expression of RBM15 and YTHDC1 and explored the immune infiltration characteristics between clusters as well as the expression of RBM15 and YTHDC1 in the clusters. YTHDC1 was finally identified as an immune biomarker for IVDD. We finally found that YTHDC1 may influence the immune microenvironment of IVDD through ABL1 and TXK. In summary, our results suggest that YTHDC1 is a potential biomarker for the development of IVDD and may provide new insights for the precise prevention and treatment of IVDD

The effects of chondroitin and/or glucosamine on patients with Kashin-Beck disease

Kashin-Beck disease (KBD), an endemic disease, is a special type of osteoarthritis (OA). Nowadays, due to prevention and treatment methods including selenium supplements, changing grains and water source as well as health education, the morbidity of KBD is reduced significantly as compared to that in the 1950s. However, many elderly adult KBD patients are still suffering from the degenerative changes of cartilage, pain, stiffness and deformation of joints, which are quite similar or even more serious than OA. Chondroitin sulfate and glucosamine have been widely used as symptomatic slow-acting drugs for the treatment of OA. Although their therapeutic effects, biochemical data, pharmacokinetics, preclinical studies, safety and economic evaluation have been well investigated in OA, they are not clearly studied in KBD. In this review, we will evaluate the clinical evidence (randomized controlled trials and non-randomized controlled trials), safeties and cost-effectiveness of chondroitin sulfate and glucosamine for the treatment of KBD. Moreover, the therapeutic mechanisms of chondroitin sulfate and glucosamine are also discussed in details