Gut microbiome-based noninvasive diagnostic model to predict acute coronary syndromes

BackgroundPrevious studies have shown that alterations in the gut microbiota are closely associated with Acute Coronary Syndrome (ACS) development. However, the value of gut microbiota for early diagnosis of ACS remains understudied.MethodsWe recruited 66 volunteers, including 29 patients with a first diagnosis of ACS and 37 healthy volunteers during the same period, collected their fecal samples, and sequenced the V4 region of the 16S rRNA gene. Functional prediction of the microbiota was performed using PICRUSt2. Subsequently, we constructed a nomogram and corresponding webpage based on microbial markers to assist in the diagnosis of ACS. The diagnostic performance and usefulness of the model were analyzed using boostrap internal validation, calibration curves, and decision curve analysis (DCA).ResultsCompared to that of healthy controls, the diversity and composition of microbial community of patients with ACS was markedly abnormal. Potentially pathogenic genera such as Streptococcus and Acinetobacter were significantly increased in the ACS group, whereas certain SCFA-producing genera such as Blautia and Agathobacter were depleted. In addition, in the correlation analysis with clinical indicators, the microbiota was observed to be associated with the level of inflammation and severity of coronary atherosclerosis. Finally, a diagnostic model for ACS based on gut microbiota and clinical variables was developed with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.963 (95% CI: 0.925–1) and an AUC value of 0.948 (95% CI: 0.549–0.641) for bootstrap internal validation. The calibration curves of the model show good consistency between the actual and predicted probabilities. The DCA showed that the model had a high net clinical benefit for clinical applications.ConclusionOur study is the first to characterize the composition and function of the gut microbiota in patients with ACS and healthy populations in Southwest China and demonstrates the potential effect of the microbiota as a non-invasive marker for the early diagnosis of ACS

Immunogenicity and safety of an inactivated enterovirus 71 vaccine coadministered with trivalent split-virion inactivated influenza vaccine: A phase 4, multicenter, randomized, controlled trial in China

BackgroundFew data exist on the immunogenicity and safety of an inactivated enterovirus 71 vaccine (EV71 vaccine) coadministered with trivalent split-virion inactivated influenza vaccine (IIV3) in infants.MethodsThis trial was a phase 4, randomized, controlled trial. Infants aged 6-11 months were eligible, with no history of hand, foot and mouth disease (HFMD) and no history of EV71 vaccine or any influenza vaccine. Eligible infants were randomly assigned to EV71+IIV3 group, EV71 group or IIV3 group. Blood samples were collected on day 0 and 56.ResultsBetween September 2019 and June 2020, 1151 infants met eligibility criteria and 1134 infants were enrolled. 1045 infants were included in the per-protocol population, including 347 in the EV71+IIV3 group, 343 in the EV71 group, and 355 in the IIV3 group. The seroconversion rate (98.56% vs 98.54%; seroconversion rates difference of 0.02% [95% CI: 0.70-0.98]) and GMT (419.05 vs 503.72; GMT ratio of 0.83 [95% CI 0.70 - 0.98]) of EV71 neutralizing antibodies in the EV71+IIV3 group was not inferior to those in the EV71 group. The non-inferiority results for influenza virus antibodies (A/H1N1, A/H3N2 and B) showed that the seroconversion rates and GMTs of the EV71+IIV3 group were non-inferiority to those of the IIV3 group. Systemic and local adverse event rates were similar between groups. None of serious adverse events (SAEs) were related to vaccination.ConclusionsCoadministration of the EV71 vaccine with IIV3 was safe and did not interfere with immunogenicity. These findings support a viable immunization strategy for infants with the EV71 vaccine coadministered with IIV3 in China. This trial is registered with ClinicalTrials.gov, number NCT04091880

Data Quality Assessment of Time-Variable Surface Microgravity Surveys in the Southeastern Tibetan Plateau

Ground-based time-variable gravimetry with high accuracy is an important approach in monitoring geodynamic processes. The uncertainty of instruments including scale factor (SF) and drift rate are the primary factors affect the quality of observation data. Differing from the conventional gravity adjustment procedure, this study adopted the modified Bayesian gravity adjustment (MBGA) method, which accounts for the nonlinear drift rate, and where the SF is considered as one of the hyperparameters estimated using Akaike’s Bayesian information criterion. Based on the terrestrial time-variable gravity datasets (2018–2020) from the southeastern Tibetan Plateau, errors caused by nonlinear drift rate and SF were processed quantitatively through analysis of the gravity difference (GD) residuals and the mutual difference of the GD. Additionally, cross validation from absolute gravity (AG) values was also applied. Results suggest that: (1) the drift rate of relavive instruments show nonlinear characteristics, and owing to their different spring features, the drift rate of CG-5 is much larger than that of LCR-G gravimeters; (2) the average bias between the original and optimized SF of the CG-5 gravimeters is approximately 169 ppm, while that of the LCR-G is no more than 63 ppm; (3) comparison of the differences in gravity values (GV) suggests that the uncertainty caused by the nonlinear drift rate is smaller than that attributable to SF. Overall, the novel approach adopted in this study was found effective in removing errors, and shown to be adaptive and robust for large-scale hybrid surface gravity campaign which providing high accuracy gravity data for the geoscience research

Effects of salt stress on the leaf shape and scaling of pyrus betulifolia bunge

CITATION: Yu, X., et al. 2019. Effects of salt stress on the leaf shape and scaling of pyrus betulifolia bunge. Symmetry, 11(8):991, doi:10.3390/sym11080991.The original publication is available at https://www.mdpi.comLeaf shape can reflect the survival and development of plants in different environments. In particular, leaf area, showing a scaling relationship with other leaf-shape indices, has been used to evaluate the extent of salt stress on plants. Based on the scaling relationships between leaf area and other leaf-shape indices in experiments at different levels of salt stress, we could examine which leaf-shape indices are also related to salt stress. In the present study, we explored the effects of different salt concentration treatments on leaf dry mass per unit area (LMA), the quotient of leaf perimeter and leaf area (QPA), the quotient of leaf width and length (QWL), the areal quotient (AQ) of left and right sides of a leaf and the standardized index (SI) for bilateral symmetry. We treated Pyrus betulifolia Bunge under NaCl salt solution of 2‰, 4‰ and 6‰, respectively, with fresh water with no salt as the control. The reduced major axis (RMA) was used to fit a linear relationship of the log-transformed data between any leaf trait measures and leaf area. We found that leaf fresh weight and dry weight decrease with salt concentration increasing, whereas the exponents of leaf dry weight versus leaf area exhibit an increasing trend, which implies that the leaves expanding in higher salt environments are prone to have a higher cost of dry mass investment to increase per unit leaf area than those in lower salt environments. Salt concentration has a significant influence on leaf shape especially QWL, and QWL under 6‰ concentration treatment is significantly greater than the other treatments. However, there is no a single increasing or decreasing trend for the extent of leaf bilateral symmetry with salt concentration increasing. In addition, we found that the scaling exponents of QPA versus leaf area for four treatments have no significant difference. It indicates that the scaling relationship of leaf perimeter versus leaf area did not change with salt concentration increasing. The present study suggests that salt stress can change leaf functional traits especially the scaling relationship of leaf dry weight versus leaf area and QWL, however, it does not significantly affect the scaling relationships between leaf morphological measures (including QPA and the extent of leaf bilateral symmetry) and leaf area.https://www.mdpi.com/2073-8994/11/8/991Publisher's versio

The Shift in Key Functional Traits Caused by Precipitation under Nitrogen and Phosphorus Deposition Drives Biomass Change in <i>Leymus chinensis</i>

The trade-offs between key functional traits in plants have a decisive impact on biomass production. However, how precipitation and nutrient deposition affect the trade-offs in traits and, ultimately, productivity is still unclear. In the present study, a mesocosm experiment was conducted to explore the relationships between biomass production and the aboveground and belowground key functional traits and their trade-offs under changes in precipitation and nutrient depositions in Leymus chinensis, a monodominant perennial rhizome grass widespread in the eastern Eurasian steppe. Our results showed that moisture is the key factor regulating the effect of nitrogen (N) and phosphorus (P) deposition on increased biomass production. Under conditions of average precipitation, water use efficiency (WUE) was the key trait determining the biomass of L. chinensis. There were obvious trade-offs between WUE and leaf area, specific leaf area, leaf thickness, and leaf dry matter. Conversely, under increasing precipitation, the effect of restricted soil water on leaf traits was relieved; the key limiting trait changed from WUE to plant height. These findings indicate that the shift of fundamental traits of photosynthetic carbon gain induced by precipitation under N and P deposition is the key ecological driving mechanism for the biomass production of typical dominant species in semi-arid grassland

The Domain Decomposition Method With Adaptive Time Step for the Transient Thermal Analysis of 3-D ICs

With the continuous emergence of various advanced packaging technologies such as copper interconnection and 3-D packaging technology, it is essential to efficiently and accurately investigate the thermal analysis of high-performance, high-power and complicated electronic devices to better design heat dissipation structures. However, multiscale transient thermal analysis of complex electronic devices by existing numerical methods is still a challenge. In this work, the 3-D domain decomposition method (DDM) with the adaptive time step for the transient thermal analysis of integrated circuits (ICs) is proposed to tackle this problem. By flexible multiscale mesh generation and automatically time step changes based on posteriori errors, the new method significantly improves computational efficiency. Some illustrative numerical examples are presented to verify the accuracy and efficiency of the proposed method by considering 3-D transient heat transfer with thermal conduction, natural convection and radiation boundaries