To study the relationship between clinical indexes and the severity of coronavirus disease 2019 (COVID‐19), and to explore its role in predicting the severity of COVID‐19. Clinical data of 443 patients with COVID‐19 admitted to our hospital were retrospectively analyzed, which were divided into nonsevere group (n = 304) and severe group (n = 139) according to their condition. Clinical indicators were compared between different groups. The differences in sex, age, the proportion of patients with combined heart disease, leukocyte, neutrophil‐to‐lymphocyte ratio (NLR), neutrophil, lymphocyte, platelet, D‐dimer, C‐reactive protein (CRP), procalcitonin, lactate dehydrogenase, and albumin on admission between the two groups were statistically significant (P  <  .05). Multivariate logistic regression analysis showed NLR and CRP were independent risk factors for severe COVID‐19. Platelets were independent protective factors for severe COVID‐19. The receiver operating characteristic (ROC) curve analysis demonstrated area under the curve of NLR, platelet, CRP, and combination was 0.737, 0.634, 0.734, and 0.774, respectively. NLR, CRP, and platelets can effectively assess the severity of COVID‐19, among which NLR is the best predictor of severe COVID‐19, and the combination of three clinical indicators can further predict severe COVID‐19.

Coronavirus disease 2019 (COVID-19) is a highly infective disease caused by the severe acute respiratory syndrome coronavirus 2 virus (SARS-CoV-2). Previous studies on COVID-19 pneumonia outbreak were based on information from the general population.

In this study, a novel poly (vinyl alcohol) (PVA)/poly (ethylene glycol) (PEG) scaffold was carefully designed via thermal processing and subsequent supercritical fluid (SCF) foaming. Interestingly, a bimodal open-celled structure with interconnected networks was successfully created in the plasticized PVA (WPVA)/PEG scaffold. Large cells were produced from the nucleation sites generated in the PVA phase during rapid depressurization, while plenty of small pores generate in the cell walls of the big cells. The formation mechanism of this cellular structure was studied by considering the various phase morphologies and the diffusion behaviour of the carbon dioxide (CO 2 ) in individual phases. In addition, the intermolecular interactions of the WPVA/PEG blend were studied using X-ray diffraction and FTIR analysis. The results demonstrate that various types of hydrogen bonds among the hydroxyl groups on the PVA chains, PEG and water molecules are formed in the blend system. The realization of thermoplastic foaming of the PVA/PEG blend benefits from the interactions of complexation and plasticization between water and PEG molecules. The SEM images also revealed that L929 fibroblast cells were able to attach and spread on surfaces of the WPVA/PEG samples. Thus the WPVA/PEG scaffold with unique bimodal cellular structure is nontoxic and favours the attachment and proliferation of cells, making it promising for use as the candidate for tissue engineering applications.

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has been identified as an important anti-inflammatory and anti-fibrotic factor. This study determined how the ACE2-Ang-(1-7)-Mas axis affected M1/ M2 macrophage polarization and thus contributed to anti-inflammatory processes in the cecal ligation and puncture (CLP)-induced inflammation model. Materials and Methods: ELISA, western blotting, and qRT-PCR were used to verify that Ang-(1-7) decreased the expression of pro-inflammatory cytokines and increased anti-inflammatory cytokines. The differentiation of M1/M2 macrophages was assessed by flow cytometry for assessing the cell-surface markers, CD86 and CD206. The related key receptors and pathways were analyzed by Western blotting, qRT-PCR, and immunofluorescence. CLP-induced inflammatory mice models were used for in vivo studies. Hematoxylin and eosin and immunohistochemical and immunofluorescence staining protocols were used to analyze histological changes in the spleen, and the related key pathway proteins were analyzed by western blotting. Results: Ang-(1-7) decreased the expressions of the TNF-α and IL-6 pro-inflammatory cytokines and increased the expressions of the IL-4 and IL-10 anti-inflammatory cytokines. INOS and TNFα, which represented M1 macrophage polarization, were decreased by Ang-(1-7). ARG1 and CD163, which represented M2 macrophage polarization, were increased by Ang-(1-7). Both Mas receptor and ACE2 are expressed on macrophages. Furthermore, the ACE2-Ang-(1-7)-MAS axis modulated macrophage polarization by ameliorating TLR4 expression and regulating the NF-кB and MAPK pathways. In addition, splenomegaly and macrophage infiltration were observed in the spleen of the CLP-induced mouse models and macrophages in the spleen suspension of CLP models were shifted to M1 phenotype and were effectively inhibited by Ang-(1-7) via the TLR4mediated NF-кB and MAPK pathways, which could be partially rescued by A-779. Ang-(1-7) inhibited inflammatory responses in vivo and in vitro, and repressed macrophage polarization toward the M1 phenotype and promoted it toward the M2 phenotype, which provided new evidence for the anti-inflammation activity of the ACE2-Ang -(1-7)-MAS axis. Conclusion:

Objective We retrospectively analyzed the data of 32 hemodialysis patients with COVID-19 to clarify the epidemiological characteristics of this special population. Method The data of 32 hemodialysis patients with COVID-19, including epidemiological, demographic, clinical, laboratory, and radiological, were collected from the Blood Purification Department of Wuhan Fourth Hospital from February 3 to 16, 2020. Results Of the 32 patients, 23 were male, and the median age was 58 years; the median dialysis vintage was 33 months. Two groups were divided according to the patient's primary renal disease: group 1 (16 patients with diabetic nephropathy), group 2 (12 patients with primary glomerulonephritis, 2 with obstructive kidney disease, 1 with hypertensive renal damage, and 1 with polycystic kidney). No significant differences were observed between the two groups in epidemiological characteristics, blood cell counts, and radiological performance. Hemodialysis patients are susceptible to COVID-19 at all ages, and patients with diabetes may be a high-risk population (50%). Common symptoms included fever (15 cases), cough (21 cases), and fatigue (7 cases). The blood lymphocyte count decreased in 84.6% of the patients (median: 0.765 × 10 9 /L). Chest CT revealed ground-glass-like lesions in 18 cases, unilateral lung patchiness in 7 cases, bilateral lung patchiness in 7 cases, and pleural effusion in 2 cases. Conclusion Only 46.875% of the hemodialysis patients with COVID-19 had fever in the early stage; and diabetics may be the most susceptible population. A decrease in blood lymphocyte count and ground-glass opacity on chest CT scan is beneficial in identifying the high-risk population.

The purpose of this study was to explore the relationship between SF3B1 mutations and the prognoses of patients with breast cancer. Clinical and SF3B1 mutation data from The Cancer Genome Atlas were analyzed. SF3B1 mutations were evaluated as prognostic factors in all breast cancer patients and specific subgroups through Cox regression and Kaplan-Meier analyses. We also investigated the relationship between traditional parameters and SF3B1 mutations. Receiver operating characteristics curves were used to analyze common risk factors for their sensitivity and specificity in predicting SF3B1 mutations. SF3B1 mutations were a poor prognostic factor in luminal B and progesterone receptor (PR)-negative breast cancer (P < 0.01). Age at diagnosis and estrogen receptor (ER) status were associated with SF3B1 mutations in all breast cancers (P < 0.01) and in luminal B and PR-negative subgroups (P < 0.01). The age at diagnosis and ER status combined had a higher sensitivity and specificity for predicting SF3B1 mutations than each factor alone. SF3B1 mutations are a poor prognostic factor in luminal B and PR-negative breast cancer patients. These mutations are significantly associated with age at diagnosis and ER status. SF3B1 mutations may therefore be a novel therapeutic target for breast cancer patients.

Rural migrants in China often face obstacles that prevent them from integrating economically and socially into their host cities. We explore the effects of host city-specific factors on the social integration of migrant workers in this article. To do this, we use a survey data set that includes a sample of migrants in nine cities in eastern and central China. We estimate a multilevel linear model (MLM), taking into account both individual and city characteristics; in the first place, we show that female, highly educated migrants who accompany their family members to new host cities are most easily integrated into local society. Regarding city-specific factors, individuals who move into urban areas within their own provinces where the dialect is similar and there is a relatively small existing rural migrant population tend to more easily integrate. We show that the economic conditions of a host city can exert both positive and negative effects on social integration.The social integration of rural migrants into host cities has become an urbanization challenge in China over the last 10 years. Data show that there were 169.3 million such rural migrants nationally in 2016 (National Bureau of Statistics of China, 2016); this has become an issue because internal migrants who are mostly from rural areas often have to endure disadvantaged and marginalized social positions in their host cities, disproportionate to their enormous contributions to burgeoning urban economies (K. H. Zhang & Song, 2003). Rural-urban migrant workers usually accept so-called 3D jobs-that is, jobs that are dirty, dangerous, and demeaning (Meng, 2012)-in order to have a reasonable quality of life, settle down, and integrate economically and socially into urban society (Y. Zhu, 2007).The problem of social integration has attracted attention from policymakers and researchers in recent years (Li, 2006;Wang & Fan, 2012;Yue, Li, & Feldman, 2016). In this context, literature and policy debates have often focused on the incompatibility of individual characteristics usually possessed by migrants with urban economies (Y. Zhu & Chen, 2010), including narrow social networks (Yue, Li, Jin, & Feldman, 2013) and their limited social participation in neighborhoods (Wu, 2012), as well as wide institutional restrictions such as the national household registration (hukou) system (Chan, 2010). In addition to these factors, host city characteristics are important in this context because these will shape a migration experience (Brettell, 2003;Massey, 1990). These features have, however, to date not been fully addressed in the literature. The goal of this article is therefore to explore the contextual effects of socioeconomic conditions, demographic composition, institutions, and the culture of host cities on the integration of migrants. This is achieved via a multilevel modeling methodology that enables us to incorporate both individual and city-specific CONTACT Ming Tian