The signal pathways and treatment of cytokine storm in COVID-19

The Coronavirus Disease 2019 (COVID-19) pandemic has become a global crisis and is more devastating than any other previous infectious disease. It has affected a significant proportion of the global population both physically and mentally, and destroyed businesses and societies. Current evidence suggested that immunopathology may be responsible for COVID-19 pathogenesis, including lymphopenia, neutrophilia, dysregulation of monocytes and macrophages, reduced or delayed type I interferon (IFN-I) response, antibody-dependent enhancement, and especially, cytokine storm (CS). The CS is characterized by hyperproduction of an array of pro-inflammatory cytokines and is closely associated with poor prognosis. These excessively secreted pro-inflammatory cytokines initiate different inflammatory signaling pathways via their receptors on immune and tissue cells, resulting in complicated medical symptoms including fever, capillary leak syndrome, disseminated intravascular coagulation, acute respiratory distress syndrome, and multiorgan failure, ultimately leading to death in the most severe cases. Therefore, it is clinically important to understand the initiation and signaling pathways of CS to develop more effective treatment strategies for COVID-19. Herein, we discuss the latest developments in the immunopathological characteristics of COVID-19 and focus on CS including the current research status of the different cytokines involved. We also discuss the induction, function, downstream signaling, and existing and potential interventions for targeting these cytokines or related signal pathways. We believe that a comprehensive understanding of CS in COVID-19 will help to develop better strategies to effectively control immunopathology in this disease and other infectious and inflammatory diseases

Macrophage migration inhibitory factor may play a protective role in osteoarthritis

Background Osteoarthritis (OA) is the most prevalent form of arthritis and the major cause of disability and overall diminution of quality of life in the elderly population. Currently there is no cure for OA, partly due to the large gaps in our understanding of its underlying molecular and cellular mechanisms. Macrophage migration inhibitory factor (MIF) is a procytokine that mediates pleiotropic inflammatory effects in inflammatory diseases such as rheumatoid arthritis (RA) and ankylosing spondylitis (AS). However, data on the role of MIF in OA is limited with conflicting results. We undertook this study to investigate the role of MIF in OA by examining MIF genotype, mRNA expression, and protein levels in the Newfoundland Osteoarthritis Study. Methods One hundred nineteen end-stage knee/hip OA patients, 16 RA patients, and 113 healthy controls were included in the study. Two polymorphisms in the MIF gene, rs755622, and -794 CATT5-8, were genotyped using polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) and PCR followed by automated capillary electrophoresis, respectively. MIF mRNA levels in articular cartilage and subchondral bone were measured by quantitative polymerase chain reaction. Plasma concentrations of MIF, tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and interleukin-1 beta (IL-1β) were measured by enzyme-linked immunosorbent assay. Results rs755622 and -794 CATT5-8 genotypes were not associated with MIF mRNA or protein levels or OA (all p ≥ 0.19). MIF mRNA level in cartilage was lower in OA patients than in controls (p = 0.028) and RA patients (p = 0.004), while the levels in bone were comparable between OA patients and controls (p = 0.165). MIF protein level in plasma was lower in OA patients than in controls (p = 3.01 × 10−10), while the levels of TNF-α, IL-6 and IL-1β in plasma were all significantly higher in OA patients than in controls (all p ≤ 0.0007). Multivariable logistic regression showed lower MIF and higher IL-1β protein levels in plasma were independently associated with OA (OR per SD increase = 0.10 and 8.08; 95% CI = 0.04–0.19 and 4.42–16.82, respectively), but TNF-α and IL-6 became non-significant. Conclusions Reduced MIF mRNA and protein expression in OA patients suggested MIF might have a protective role in OA and could serve as a biomarker to differentiate OA from other joint disorders

Recrystallization Mechanism and Processing Map of 18CrNiMo7-6 Alloy Steel during Hot Deformation

In this study, isothermal single-pass forming doformation of forged 18CrNiMo7-6 alloy steel was carried out by Gleeble-3500 thermal simulation testing machine. The constitutive equations and processing maps with parameters of deformation temperature and strain rate were established. The results show that the optimum hot deformation parameters are temperature 1050 °C, strain rate 0.1 s–1 with the peak power efficiency being 0.432. The mechanism of grain refinement during hot compression was also characterized by electron backscatter diffraction (EBSD). The results show that continuous dynamic recrystallization (CDRX), discontinuous dynamic recrystallization (DDRX) and grain growth are the main microstructure evolution mechanisms during hot working. The rotation of sub-grains under CDRX mechanism is the main factor for the formation of new grains. In addition, the DDRX mechanism is formed by the bulging of HAGBs at the grain boundary triple junction of the original grains, and the CDRX mechanism forms finer grains. The study also found that temperature affected the organization evolution mechanism, the DDRX mechanism plays a leading role when the temperature is low. With the increase of deformation temperature, CDRX begins to play a leading role and forms finer grains. When the deformation temperature rises to 1150 °C, the grains continue to grow at a higher temperature

Mechanical Characteristics of Structures and Ground Deformation Caused by Shield Tunneling Under-Passing Highways in Complex Geological Conditions Based on the MJS Method

This study defined the height ratio of soft-rock strata and established a numerical model for analyzing shield construction in upper-soft, lower-hard composite strata together with field monitoring data. In this way, the influence of shield tunneling while passing under the pile foundation of the culvert at a short distance (the shortest distance is 1.4 m) in the typical upper-soft, lower-hard composite strata in Guangzhou can be examined. Moreover, the reinforcement effects of the ground, the bridges, and the culverts, using the strata-reinforcing plan dominated by the metro jet system (MJS) in a narrow space, are evaluated. Based on the results, (i) the maximum ground subsidence is found at the position in which the height ratio of the soft rock is 1.0. (ii) However, differential subsidence might be found in the subsequent shield construction when the soft-rock height ratio of the adjacent excavated surface ranges from 0 to 0.2 and from 0.5 to 1. (iii) The concentrated release of stress has a greater impact on the structure than the geological conditions of the shield tunneling face. (iv) Reinforcing with the MJS method contains the concentrated release of stress. This study can provide a reference for controlling the deformation of the under-crossing structure in the shield construction of the upper-soft, lower-hard composite strata

New record of fossil wood Xenoxylon from the Late Triassic in the Sichuan Basin, southern China and its paleoclimatic implications

International audienc

Serum Metabolomic Signatures for Knee Cartilage Volume Loss over 10 Years in Community-Dwelling Older Adults

Osteoarthritis (OA) is the most prevalent joint disorder characterized by joint structural pathological changes with the loss of articular cartilage as its hallmark. Tools that can predict cartilage loss would help identify people at high risk, thus preventing OA development. The recent advance of the metabolomics provides a new avenue to systematically investigate metabolic alterations in disease and identify biomarkers for early diagnosis. Using a metabolomics approach, the current study aimed to identify serum metabolomic signatures for predicting knee cartilage volume loss over 10 years in the Tasmania Older Adult Cohort (TASOAC). Cartilage volume was measured in the medial, lateral, and patellar compartments of the knee by MRI at baseline and follow-up. Changes in cartilage volume over 10 years were calculated as percentage change per year. Fasting serum samples collected at 2.6-year follow-up were metabolomically profiled using the TMIC Prime Metabolomics Profiling Assay and pairwise metabolite ratios as the proxies of enzymatic reaction were calculated. Linear regression was used to identify metabolite ratio(s) associated with change in cartilage volume in each of the knee compartments with adjustment for age, sex, and BMI. The significance level was defined at α = 3.0 × 10−6 to control multiple testing. A total of 344 participants (51% females) were included in the study. The mean age was 62.83 ± 6.13 years and the mean BMI was 27.48 ± 4.41 kg/m2 at baseline. The average follow-up time was 10.84 ± 0.66 years. Cartilage volume was reduced by 1.34 ± 0.72%, 1.06 ± 0.58%, and 0.98 ± 0.46% per year in the medial, lateral, and patellar compartments, respectively. Our data showed that the increased ratios of hexadecenoylcarnitine (C16:1) to tetradecanoylcarnitine (C14) and C16:1 to dodecanoylcarnitine (C12) were associated with 0.12 ± 0.02% reduction per year in patellar cartilage volume (both p < 3.03 × 10−6). In conclusion, our data suggested that alteration of long chain fatty acid β-oxidation was involved in patellar cartilage loss. While confirmation is needed, the ratios of C16:1 to C14 and C12 might be used to predict long-term cartilage loss

Ground Radioactivity Distribution Reconstruction and Dose Rate Estimation Based on Spectrum Deconvolution

Estimating the gamma dose rate at one meter above ground level and determining the distribution of radioactive pollution from aerial radiation monitoring data are the core technical issues of unmanned aerial vehicle nuclear radiation monitoring. In this paper, a reconstruction algorithm of the ground radioactivity distribution based on spectral deconvolution was proposed for the problem of regional surface source radioactivity distribution reconstruction and dose rate estimation. The algorithm estimates unknown radioactive nuclide types and their distributions using spectrum deconvolution and introduces energy windows to improve the accuracy of the deconvolution results, achieving accurate reconstruction of multiple continuous distribution radioactive nuclides and their distributions, as well as dose rate estimation of one meter above ground level. The feasibility and effectiveness of the method were verified through cases of single-nuclide (137Cs) and multi-nuclide (137Cs and 60Co) surface sources by modeling and solving them. The results showed that the cosine similarities between the estimated ground radioactivity distribution and dose rate distribution with the true value were 0.9950 and 0.9965, respectively, which could prove that the proposed reconstruction algorithm would effectively distinguish multiple radioactive nuclides and accurately restore their radioactivity distribution. Finally, the influences of statistical fluctuation levels and the number of energy windows on the deconvolution results were analyzed, showing that the lower the statistical fluctuation level and the more energy window divisions, the better the deconvolution results

Revealing the aging process of solid electrolyte interphase on SiOx anode

Abstract As one of the most promising alternatives to graphite negative electrodes, silicon oxide (SiO x ) has been hindered by its fast capacity fading. Solid electrolyte interphase (SEI) aging on silicon SiO x has been recognized as the most critical yet least understood facet. Herein, leveraging 3D focused ion beam-scanning electron microscopy (FIB-SEM) tomographic imaging, we reveal an exceptionally characteristic SEI microstructure with an incompact inner region and a dense outer region, which overturns the prevailing belief that SEIs are homogeneous structure and reveals the SEI evolution process. Through combining nanoprobe and electron energy loss spectroscopy (EELS), it is also discovered that the electronic conductivity of thick SEI relies on the percolation network within composed of conductive agents (e.g., carbon black particles), which are embedded into the SEI upon its growth. Therefore, the free growth of SEI will gradually attenuate this electron percolation network, thereby causing capacity decay of SiO x . Based on these findings, a proof-of-concept strategy is adopted to mechanically restrict the SEI growth via applying a confining layer on top of the electrode. Through shedding light on the fundamental understanding of SEI aging for SiO x anodes, this work could potentially inspire viable improving strategies in the future