TEMPO-Oxidized Nanocellulose Films Modified by Tea Saponin Derived from Camellia oleifera: Physicochemical, Mechanical, and Antibacterial Properties.

Nanocellulose materials have been widely used in biomedicine, food packaging, aerospace, composite material, and other fields. In this work, cellulose obtained from Camellia shells through alkali boiling and subbleaching was micro-dissolved and regenerated using the DMAc (N,N-Dimethylacetamide)/LiCl system, and TOCNs (TEMPO-oxidized cellulose nanofibers) with different degrees of oxidation. The membrane was prepared by filtration of polytetrafluoroethylene (pore size 0.1 µm), and the oxidized nanocellulose film was obtained after drying, Then, the crystallinity, mechanical properties and oxygen barrier properties of the TOCN film were investigated. Furthermore, based on TS (tea saponin) from Camellia oleifera seed cake and TOCNs, TS-TOCN film was prepared by the heterogeneous reaction. The TS-TOCN film not only shows excellent oxygen barrier properties (the oxygen permeability is 2.88 cc·m-2·d-1) but also has good antibacterial effects on both Gram-negative and Gram-positive bacteria. The antibacterial property is comparable to ZnO-TOCN with the same antibacterial content prepared by the in-situ deposition method. Antioxidant activity tests in vitro showed that TS-TOCN had a significant scavenging effect on DPPH (2,2-Diphenyl-1-picrylhydrazyl) radicals. This design strategy makes it possible for inexpensive and abundant Camellia oleifera remainders to be widely used in the field of biobased materials.

Analysis of spatial-temporal dynamic distribution and related factors of tuberculosis in China from 2008 to 2018.

Through spatial-temporal scanning statistics, the spatial-temporal dynamic distribution of pulmonary tuberculosis incidence in 31 provinces and autonomous regions of China from 2008 to 2018 is obtained, and the related factors of spatial-temporal aggregation of tuberculosis in China are analyzed to provide strong scientific basis and data support for the prevention and control of pulmonary tuberculosis. This is a retrospective study, using spatial epidemiological methods to reveal the spatial-temporal clustering distribution characteristics of China's tuberculosis epidemic from 2008 to 2018, in which cases data comes from the China Center for Disease Control and prevention. Office Excel is used for general statistical description, and the single factor correlation analysis adopts χ2 Test (or trend χ2 Inspection). Retrospective discrete Poisson distribution space time scanning statistics of SaTScan 9.6 software are used to analyze the space time dynamic distribution of tuberculosis incidence in 31 provinces, cities and autonomous regions in China from 2008 to 2018. ArcGIS 10.2 software is used to visualize the results. The global spatial autocorrelation analysis adopts Moran's I of ArcGIS Map(Monte Carlo randomization simulation times of 999) is used to analyze high-risk areas, low-risk areas and high-low risk areas. From 2008 to 2018, 10,295,212 cases of pulmonary tuberculosis were reported in China, with an average annual incidence rate of 69.29/100,000 (95% CI: (69.29 ± 9.16)/100,000). The annual GDP (gross domestic product) of each province and city showed an upward trend year by year, and the number of annual medical institutions in each province and city showed a sharp increase in 2009, and then tended to be stable; From 2008 to 2018, the national spatiotemporal scanning statistics scanned a total of 6 clusters, including 23 provinces and cities. The national high-low spatiotemporal scanning statistics of the number of pulmonary tuberculosis cases scanned a total of 2 high-risk and low-risk clusters. The high-risk cluster included 8 provinces and cities, and the low-risk cluster included 12 provinces and cities. The global autocorrelation Moran's I index of the incidence rate of pulmonary tuberculosis in all provinces and cities was greater than the expected value (E (I) = -0.0333); The correlation analysis between the average annual GDP and the number of pulmonary tuberculosis cases in each province and city from 2008 to 2018 was statistically significant. From 2008 to 2018, the spatial and temporal scanning and statistical scanning areas of tuberculosis incidence in China were mainly concentrated in the northwest and southern regions of China. There is an obvious positive spatial correlation between the annual GDP distribution of each province and city, and the aggregation degree of the development level of each province and city is increasing year by year. There is a correlation between the average annual GDP of each province and the number of tuberculosis cases in the cluster area. There is no correlation between the number of medical institutions set up in each province and city and the number of pulmonary tuberculosis cases.

Monitoring European data with prospective space-time scan statistics: predicting and evaluating emerging clusters of COVID-19 in European countries.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has become a pandemic infectious disease and become a serious public health crisis. As the COVID-19 pandemic continues to spread, it is of vital importance to detect COVID-19 clusters to better distribute resources and optimizing measures. This study helps the surveillance of the COVID-19 pandemic and discovers major space-time clusters of reported cases in European countries. Prospective space-time scan statistics are particularly valuable because it has detected active and emerging COVID-19 clusters. It can prompt public health decision makers when and where to improve targeted interventions, testing locations, and necessary isolation measures, and the allocation of medical resources to reduce further spread. METHODS: Using the daily case data of various countries provided by the European Centers for Disease Control and Prevention, we used SaTScan™ 9.6 to conduct a prospective space-time scan statistics analysis. We detected statistically significant space-time clusters of COVID-19 at the European country level between March 1st to October 2nd, 2020 and March 1st to October 2nd, 2021. Using ArcGIS to draw the spatial distribution map of COVID-19 in Europe, showing the emerging clusters that appeared at the end of our study period detected by Poisson prospective space-time scan statistics. RESULTS: The results show that among the 49 countries studied, the regions with the largest number of reported cases of COVID-19 are Western Europe, Central Europe, and Eastern Europe. Among the 49 countries studied, the country with the largest cumulative number of reported cases is the United Kingdom, followed by Russia, Turkey, France, and Spain. The country (or region) with the lowest cumulative number of reported cases is the Faroe Islands. We discovered 9 emerging clusters, including 21 risky countries. CONCLUSION: This result can provide timely information to national public health decision makers. For example, a country needs to improve the allocation of medical resources and epidemic detection points, or a country needs to strengthen entry and exit testing, or a country needs to strengthen the implementation of protective isolation measures. As the data is updated daily, new data can be re-analyzed to achieve real-time monitoring of COVID-19 in Europe. This study uses Poisson prospective space-time scan statistics to monitor COVID-19 in Europe.

Biomarkers of interstitial lung disease associated with primary Sjögren's syndrome.

OBJECTIVES: The aim of this study was to investigate serum biomarkers linked to primary Sjögren's syndrome (pSS)-associated interstitial lung disease (ILD). METHODS: 69 pSS patients were consecutively enrolled and evaluated via quantitative ILD scoring based on high-resolution computed tomography (HRCT). Biomarkers of interest were assessed by multiplex enzyme-linked immunosorbent assays (ELISAs). RESULTS: Among consecutively enrolled patients with pSS, the presence of pSS-ILD was 50% based on the presence of radiographically defined interstitial lung abnormalities (ILA) meeting specified criteria for mild/moderate (ILA 2) or severe (ILA 3) disease. Age, immunoglobulin M (IgM), C-reactive protein (CRP), and serum levels of eotaxin/CCL11, Krebs von den Lungen-6 (KL-6), TNFα, and TGFα were significantly higher in the combined pSS-ILD group (ILA 2 + ILA 3) than in the pSS-no-ILD and pSS-indeterminate ILD groups (ILA 0 and ILA 1, respectively) in unadjusted analyses (p < 0.05 for all variables). A binary logistic regression model revealed that disease duration and KL-6 levels were associated with the presence of pSS-ILD (p < 0.05). Complementary least absolute shrinkage and selection operator (LASSO) modeling showed that age, KL-6, and TNF-α effectively differentiated pSS-ILD (ILA 2 + ILA3) from pSS without ILD (ILA 0 + ILA 1), with an area under the curve (AUC) of 0.883 (p value < 0.0001). CONCLUSIONS: Patient age, disease duration, and serum levels of both KL-6 and TNFα were the most discriminating factors associated with the presence of ILD in our pSS patients. Higher levels of CRP, IgM, eotaxin, TGFα, and TNFα should also prompt the search for occult as well as clinically evident lung involvement based on statistically significant univariate associations with pSS-ILD. CLINICAL TRIAL REGISTRATION: None.

Myc inhibition tips the immune balance to promote antitumor immunity.

Aberrant expression of Myc is one of the most common oncogenic events in human cancers. Scores of Myc inhibitors are currently under development for treating Myc-driven cancers. In addition to directly targeting tumor cells, Myc inhibition has been shown to modulate the tumor microenvironment to promote tumor regression. However, the effect of Myc inhibition on immune cells in the tumor microenvironment remains poorly understood. Here, we show that the adaptive immune system plays a vital role in the antitumor effect of pharmacologic inhibition of Myc. Combining genetic and pharmacologic approaches, we found that Myc inhibition enhanced CD8 T cell function by suppressing the homeostasis of regulatory T (Treg) cells and the differentiation of resting Treg (rTreg) cells to activated Treg (aTreg) cells in tumors. Importantly, we demonstrated that different Myc expression levels confer differential sensitivity of T cell subsets to pharmacologic inhibition of Myc. Although ablation of the Myc gene has been shown to suppress CD8 T cell function, Treg cells, which express much less Myc protein than CD8 T cells, are more sensitive to Myc inhibitors. The differential sensitivity of CD8 T and Treg cells to Myc inhibitors resulted in enhanced CD8 T cell function upon Myc inhibition. Our findings revealed that Myc inhibitors can induce an antitumor immune response during tumor progression.

Predictors of long-term prognosis in rheumatoid arthritis-related interstitial lung disease.

The aim of the study was to identify specific clinical and serum protein biomarkers that are associated with longitudinal outcome of RA-associated interstitial lung disease (RA-ILD). 60 RA patients with clinical and serological profiles were assessed by HRCT and pulmonary function tests (PFTs) at baseline (Year 0) and 5 years post enrollment (Year 5). Progression versus non-progression was defined based on changes in Quantitative Modified HRCT scores and PFTs over time. Specific serum protein biomarkers were assessed in serum samples at baseline and Year 5 by Multiplex enzyme-linked immunosorbent assays (ELISAs). At Year 5, 32% of patients demonstrated progressive RA-ILD, 35% were stable, and 33% improved. Baseline age and rheumatoid factor (RF) were significantly different between RA-ILD outcomes of progression vs. no-progression (p < 0.05). Changes in levels of CXCL11/I-TAC and MMP13 over 5 years also distinguished pulmonary outcomes (p < 0.05). A final binary logistic regression model revealed that baseline age and changes in serum MMP13 as well as CXCL11/I-TAC were associated with RA-ILD progression at Year 5 (p < 0.01), with an AUC of 0.7772. Collectively, these analyses demonstrated that baseline clinical variables (age, RF) and shifts in levels of selected serum proteins (CXCL11/I-TAC, MMP13) were strongly linked to RA-ILD outcome over time.

A downsampling method enables robust clustering and integration of single-cell transcriptome data.

The random noises, sampling biases, and batch effects often confound true biological variations in single-cell RNA-sequencing (scRNA-seq) data. Adjusting such biases is key to the robust discoveries in downstream analyses, such as cell clustering, gene selection and data integration. Here we propose a model-based downsampling algorithm based on minimal unbiased representative points (MURPXMBD). MURPXMBD is designed to retrieve a set of representative points by reducing gene-wise random independent errors, while retaining the covariance structure of biological origin hence provide an unbiased representation of the cell population. Subsequent validation using benchmark datasets shows that MURPXMBD can improve the quality and accuracy of clustering algorithms, and thus facilitate the discovery of new cell types. Besides, MURPXMBD also improves the performance of dataset integration algorithms. In summary, MURPXMBD serves as a useful noise-reduction method for single-cell sequencing analysis in biomedical studies.

Exposure to Tobacco Smoking Induces a subset of Activated Tumor-resident Tregs in Non-Small Cell Lung Cancer.

Tobacco smoking is the major cause of non-small-cell-lung cancer (NSCLC). However, it is barely known how smoking impact the tumor immune environment (TIME) of lung cancer. We integrated single-cell RNA-seq and bulk RNA-seq data from several studies to systematically study the impact of smoking on T cells in treatment naïve NSCLC patients. We defined a set of smoking-induced differentially expressed genes (SIDEGs) in different cells in TIME.. Specifically, we defined a smoking-related tumor-specific Treg subset, ADAM12+ CTLA4+ Tregs according to the trajectory analysis and highly express genes in cell adhesion pathways and lipid metabolism. Using independent datasets from treatment naïve patients, we found that the fraction of ADAM12+ CTLA4+ Tregs are significantly increased in patients with smoking history. Moreover, the fraction of ADAM12+ CTLA4+ Tregs are positively correlated with the fraction of exhausted T cells. Additionally, we reconstructed the spatial organization of the tumor immune microenvironment and found that ADAM12+ CTLA4+ Tregs more actively communicate with LAYN+CD8+ exhausted T cells compared with ADAM12-CTLA4+ Tregs. Our data demonstrate that smoking induced a unique subset of tumor-specific activated Tregs which interact with exhausted T cells in the TIME. Our findings not only explained how smoking impact the TIME but also provide new targets and biomarkers for precision immunotherapy of lung cancer.

Research progress of infectious disease dynamics models / 预防医学

@#The management of emerging infectious diseases has always been given a high priority in public health. Identification of the epidemiological characteristics and transmission patterns of emerging infectious diseases is of great significance to contain the disease transmission and reduce the damages to public health and socioeconomic developments. Currently, infectious disease dynamics models are mainly established based on infectious disease surveillance data to predict the epidemiological patterns and trends of emerging infectious diseases; however, many model-based predictions fail to achieve the expected results due to the presence of multiple uncertain factors during the integrated management of infectious diseases. This review describes the basic principles and variables of common infectious disease dynamics models, including the susceptible-infected-recovered ( SIR ) model, susceptible-infected-removed-susceptible ( SIRS ) model, susceptible-exposed-infected-removed ( SEIR ) model and improved SEIR model, compares the advantages and disadvantages of these models, and summarizes the advances of the infectious disease dynamics models in the prediction of trends in incidence of emerging infectious diseases, so as to provide insights into the effective application of infectious disease dynamics models in the management of infectious diseases.

Gut Microbiome Contributes to Liver Fibrosis Impact on T Cell Receptor Immune Repertoire.

Gut microbiota (GM) modifies the intrahepatic immune microenvironment, but the underlying mechanisms remain poorly understood. Liver fibrosis-associated imprinting is predicted to be reflected in GM. This study investigated the link between GM and the intrahepatic T cell receptor (TCR) immune repertoire (IR), and whether GM modulates the intrahepatic immune microenvironment via TCR IR during liver fibrosis. We analyzed the correlation between GM and TCR IR during liver fibrogenesis. Accordingly, 16S rRNA gene sequencing (16S-seq) and bulk immune repertoire sequencing (IR-seq) were performed to characterize GM and intrahepatic TCR IR. Fecal microbial transplant (FMT) and TCRß knockout (TcrbKO) mouse models were employed to determine the biological link between GM and TCR IR in liver fibrosis. We found that GM and intrahepatic TCR IR are highly correlated, with both showing reduced diversity and centralized distribution during liver fibrosis. The restoration of normal intestinal microbiota may reshape intrahepatic TCR IR and delay liver fibrosis. Interestingly, TCR IR ablation abrogated the impact of GM on liver fibrogenesis. Furthermore, GM modulated hepatic stellate cell (HSC) activation via TCR IR-mediated intrahepatic immune milieu. Our study demonstrates that GM, which exhibits cross-talk with the intrahepatic TCR IR, influences the intrahepatic immune microenvironment and liver fibrosis progression.

Cis- and Trans-Acting Expression Quantitative Trait Loci of Long Non-Coding RNA in 2,549 Cancers With Potential Clinical and Therapeutic Implications.

Many cancer risk loci act as expression quantitative trait loci (eQTLs) of transcripts including non-coding RNA. Long non-coding RNAs (lncRNAs) are implicated in various human cancers. However, the pathological and clinical impacts of the genetic determinants of lncRNAs in cancers remain largely unknown. In this study, we performed eQTL mapping of lncRNA expression (elncRNA) in 11 TCGA cancer types and characterized the biological processes of elncRNAs in the setting of genomic location, cancer treatment responses, and immune microenvironment. As a result, 10.86% of the cis-eQTLs and 1.67% of the trans-eQTLs of lncRNA were related to known genome-wide association studies (GWAS) cancer risk loci. The elncRNAs are significantly enriched for those which are previously annotated as predictive of drug sensitivities in cancer cell lines. We further revealed the downstream transcriptomic effectors of eQTL-elncRNA pairs. Our data specifically suggested that the genes affected by eQTL-elncRNA associations are enriched in the immune system processes and eQTL-elncRNA associations influence the constitution of tumor infiltrating lymphocytes. In ovarian cancer, the "rs34631313-AC092580.4" pair was associated with increased fraction of CD8+ T cells and M1 Macrophage; whereas in KIRC, the "rs9546285-LINC00426" pair was associated with increased fraction of CD8+ T cells and a decreased fraction of M2 macrophages. Our findings provide a systematic view of the transcriptomic impacts of the eQTL landscape of lncRNA in human cancers and suggest its strong potential relevance to cancer immunity and treatment.

The T Cell Receptor Immune Repertoire Protects the Liver From Reconsitution.

Aberrant immune cell infiltrates and microcircumstances represent characteristic features of liver fibrosis. In this study, we profiled the transcriptomes of intrahepatic CD45+ immune cells, from mice, using single-cell RNA sequencing (scRNA-seq) technology to understand the landscape of intrahepatic immune cells during the pathogenesis of fibrosis. Analysis of approximately 10,000 single-cell transcriptomes revealed an increase in dendritic cells (DCs), macrophages, and neutrophils and a decrease in T and natural killer T (NKT) cells. In addition, we report changes in the transcriptomes of diverse immune cell types, implying a deteriorating intrahepatic immune microcircumstance. Furthermore, we uncovered a novel fibrosis-associated CD8 T (Ccl5+, Ccl4+) and CD4 T (mt-Co1+) cell subpopulation, which infiltrates fibrotic liver and is characterized by abnormal activation or inactivation as well as a TCR decline. The results from scRNA-seq and bulk immune repertoire sequencing (IR-seq) revealed an obvious decline in T cell receptor (TCR) clonotypes combined with shrinking VJ and VDJ segment usage, as well as lower complementarity-determining region 3 (CDR3) amino acid (AA) diversity from fibrotic liver. Interestingly, a deficiency of TCR IR (TcrbKO mice) led to a deterioration of liver fibrosis, coupled with activation of hepatic stellate cells (HSCs) induced by the upregulation of macrophage and γδ T cell distribution in fibrotic TcrbKO livers. Our findings reveal the landscape and dynamics of single immune cells in liver fibrosis, and clarify the protective role of TCR IR in response to chronic liver injury.