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Chronic prostate inflammation in patients with benign prostate hyperplasia (BPH) correlates with the severity of symptoms. How inflammation contributes to prostate enlargement and/or BPH symptoms and the underlying mechanisms remain unclear. In this study, we utilize a unique transgenic mouse model that mimics chronic non-bacterial prostatitis in men and investigate the impact of inflammation on androgen receptor (AR) in basal prostate stem cells (bPSC) and their differentiation in vivo. We find that inflammation significantly enhances AR levels and activity in bPSC. More importantly, we identify interleukin 1 receptor antagonist (IL-1RA) as a crucial regulator of AR in bPSC during inflammation. IL-1RA is one of the top molecules upregulated by inflammation, and inhibiting IL-1RA reverses the enhanced AR activity in organoids derived from inflamed bPSC. Additionally, IL-1RA appears to activate AR by counteracting IL-1α's inhibitory effect. Furthermore, using a lineage tracing model, we observe that inflammation induces bPSC proliferation and differentiation into luminal cells even under castrate conditions, indicating that AR activation driven by inflammation is sufficient to promote bPSC proliferation and differentiation. Taken together, our study uncovers mechanisms through which inflammation modulates AR signaling in bPSC and induces bPSC luminal differentiation that may contribute to prostate hyperplasia. Inflammation enhances androgen receptor levels and activity in basal prostate stem cells via IL-1RA, promoting their proliferation and differentiation, potentially contributing to benign prostate hyperplasia in mice. [ABSTRACT FROM AUTHOR]

The IL-2 receptor α chain (IL-2Rα/CD25) is constitutively expressed on double-negative (DN2/DN3 thymocytes and regulatory T cells (Tregs) but induced by IL-2 on T and natural killer (NK) cells, with Il2ra expression regulated by a STAT5-dependent super-enhancer. We investigated CD25 regulation and function using a series of mice with deletions spanning STAT5-binding elements. Deleting the upstream super-enhancer region mainly affected constitutive CD25 expression on DN2/DN3 thymocytes and Tregs, with these mice developing autoimmune alopecia, whereas deleting an intronic region decreased IL-2–induced CD25 on peripheral T and NK cells. Thus, distinct super-enhancer elements preferentially control constitutive versus inducible expression in a cell type–specific manner. The mediator-1 coactivator colocalized with specific STAT5-binding sites. Moreover, both upstream and intronic regions had extensive chromatin interactions, and deletion of either region altered the super-enhancer structure in mature T cells. These results demonstrate differential functions for distinct super-enhancer elements, thereby indicating previously unknown ways to manipulate CD25 expression in a cell type–specific fashion. Editor's summary: Regulation of the gene encoding IL-2Rα (CD25) has been studied extensively to understand discrete patterns of expression on lymphocyte subsets, including the influence of Il2ra super-enhancer elements. Spolski et al. undertook an exhaustive investigation of CD25 regulation and function using a panel of mice bearing different deletions within Il2ra super-enhancer elements that modulate binding of STAT5. Deletion of the upstream super-enhancer region markedly affected constitutive CD25 expression on double-negative (DN)2/DN3 thymocytes and Tregs and resulted in the development of mice with autoimmune alopecia. By contrast, deletion of an intronic region reduced IL-2–driven CD25 expression on peripheral NK and T cells. The upstream and intronic regions also exhibited chromatin interactions, and deletions resulted in changes in super-enhancer structures in mature T cells. These findings highlight roles of different super-enhancer elements in controlling CD25 expression. —Christiana Fogg [ABSTRACT FROM AUTHOR]

Background: Infectious diseases are a major threat to public health, causing serious medical consumption and casualties. Accurate prediction of infectious diseases incidence is of great significance for public health organizations to prevent the spread of diseases. However, only using historical incidence data for prediction can not get good results. This study analyzes the influence of meteorological factors on the incidence of hepatitis E, which are used to improve the accuracy of incidence prediction. Methods: We extracted the monthly meteorological data, incidence and cases number of hepatitis E from January 2005 to December 2017 in Shandong province, China. We employ GRA method to analyze the correlation between the incidence and meteorological factors. With these meteorological factors, we achieve a variety of methods for incidence of hepatitis E by LSTM and attention-based LSTM. We selected data from July 2015 to December 2017 to validate the models, and the rest was taken as training set. Three metrics were applied to compare the performance of models, including root mean square error(RMSE), mean absolute percentage error(MAPE) and mean absolute error(MAE). Results: Duration of sunshine and rainfall-related factors(total rainfall, maximum daily rainfall) are more relevant to the incidence of hepatitis E than other factors. Without meteorological factors, we obtained 20.74%, 19.50% for incidence in term of MAPE, by LSTM and A-LSTM, respectively. With meteorological factors, we obtained 14.74%, 12.91%, 13.21%, 16.83% for incidence, in term of MAPE, by LSTM-All, MA-LSTM-All, TA-LSTM-All, BiA-LSTM-All, respectively. The prediction accuracy increased by 7.83%. Without meteorological factors, we achieved 20.41%, 19.39% for cases in term of MAPE, by LSTM and A-LSTM, respectively. With meteorological factors, we achieved 14.20%, 12.49%, 12.72%, 15.73% for cases, in term of MAPE, by LSTM-All, MA-LSTM-All, TA-LSTM-All, BiA-LSTM-All, respectively. The prediction accuracy increased by 7.92%. More detailed results are shown in results section of this paper. Conclusions: The experiments show that attention-based LSTM is superior to other comparative models. Multivariate attention and temporal attention can greatly improve the prediction performance of the models. Among them, when all meteorological factors are used, multivariate attention performance is better. This study can provide reference for the prediction of other infectious diseases. [ABSTRACT FROM AUTHOR]

We probed the lifecycle of Epstein‐Barr virus (EBV) on a cell‐by‐cell basis using single cell RNA sequencing (scRNA‐seq) data from nine publicly available lymphoblastoid cell lines (LCLs). While the majority of LCLs comprised cells containing EBV in the latent phase, two other clusters of cells were clearly evident and were distinguished by distinct expression of host and viral genes. Notably, both were high expressors of EBV LMP1/BNLF2 and BZLF1 compared to another cluster that expressed neither gene. The two novel clusters differed from each other in their expression of EBV lytic genes, including glycoprotein gene GP350. The first cluster, comprising GP350–LMP1hi cells, expressed high levels of HIF1A and was transcriptionally regulated by HIF1‐α. Treatment of LCLs with Pevonedistat, a drug that enhances HIF1‐α signaling, markedly induced this cluster. The second cluster, containing GP350+LMP1hi cells, expressed EBV lytic genes. Host genes that are controlled by super‐enhancers (SEs), such as transcription factors MYC and IRF4, had the lowest expression in this cluster. Functionally, the expression of genes regulated by MYC and IRF4 in GP350+LMP1hi cells were lower compared to other cells. Indeed, induction of EBV lytic reactivation in EBV+ AKATA reduced the expression of these SE‐regulated genes. Furthermore, CRISPR‐mediated perturbation of the MYC or IRF4 SEs in LCLs induced the lytic EBV gene expression, suggesting that host SEs and/or SE target genes are required for maintenance of EBV latency. Collectively, our study revealed EBV‐associated heterogeneity among LCLs that may have functional consequence on host and viral biology. [ABSTRACT FROM AUTHOR]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ahj.2005.02.032 Byline: Lantu Gou (a), Mingde Fu (a), Yanhua Xu (b), Ying Tian (c), Bingyu Yan (a), Luchuan Yang (a) Abstract: To investigate the alterations of high-density lipoprotein (HDL) subclasses in endogenous hypertriglyceridemic subjects. Author Affiliation: (a) Department of Biochemistry and Molecular Biology, Apolipoprotein Research Unit, West China Medical Center, Sichuan University, Chengdu, Sichuan, People's Republic of China (b) Hoist Group Postdoctoral Work Station, Chengdu, Sichuan, People's Republic of China (c) Department of Biochemistry and Molecular Biology, Nanhua University, Hengyang, Hunan, People's Republic of China Article History: Received 30 September 2004; Accepted 15 February 2005

To the Editor: Hepatitis E, caused by hepatitis E virus (HEV), is recognized as a zoonosis (1). HEV has been identified in a wide range of animals, and swine is [...]

COVID-19 hyperactivates complement: The complement system is a series of innate immune system proteins that help antibodies and phagocytes identify and eliminate pathogens. Activation of the complement system correlates with COVID-19 severity, but the cells that produce complement and potential treatments to inhibit complement activation during SARS-CoV-2 infection are not known. Here, Yan et al. used transcriptomics from patient bronchoalveolar lavage and infection models to demonstrate that SARS-CoV-2 infection induced complement-related genes and the activated complement component C3a in respiratory epithelial cells. C3a production was tied to IFN-induced JAK1/2-STAT1 signaling. Inhibition of JAK1/2 with ruxolitinib, with or without an antiviral, or a cell-permeable complement inhibitor repressed C3a production in SARS-CoV-2–infected epithelial cells. Thus, the use of JAK1/2 inhibitors may inhibit pathologies in patients with severe COVID-19. Patients with coronavirus disease 2019 (COVID-19) present a wide range of acute clinical manifestations affecting the lungs, liver, kidneys, and gut. Angiotensin-converting enzyme 2 (ACE2), the best-characterized entry receptor for the disease-causing virus SARS-CoV-2, is highly expressed in the aforementioned tissues. However, the pathways that underlie the disease are still poorly understood. Here, we unexpectedly found that the complement system was one of the intracellular pathways most highly induced by SARS-CoV-2 infection in lung epithelial cells. Infection of respiratory epithelial cells with SARS-CoV-2 generated activated complement component C3a and could be blocked by a cell-permeable inhibitor of complement factor B (CFBi), indicating the presence of an inducible cell-intrinsic C3 convertase in respiratory epithelial cells. Within cells of the bronchoalveolar lavage of patients, distinct signatures of complement activation in myeloid, lymphoid, and epithelial cells tracked with disease severity. Genes induced by SARS-CoV-2 and the drugs that could normalize these genes both implicated the interferon-JAK1/2-STAT1 signaling system and NF-κB as the main drivers of their expression. Ruxolitinib, a JAK1/2 inhibitor, normalized interferon signature genes and all complement gene transcripts induced by SARS-CoV-2 in lung epithelial cell lines but did not affect NF-κB–regulated genes. Ruxolitinib, alone or in combination with the antiviral remdesivir, inhibited C3a protein produced by infected cells. Together, we postulate that combination therapy with JAK inhibitors and drugs that normalize NF-κB signaling could potentially have clinical application for severe COVID-19. [ABSTRACT FROM AUTHOR]

Background: Accurate and reliable predictions of infectious disease can be valuable to public health organizations that plan interventions to decrease or prevent disease transmission. A great variety of models have been developed for this task. However, for different data series, the performance of these models varies. Hepatitis E, as an acute liver disease, has been a major public health problem. Which model is more appropriate for predicting the incidence of hepatitis E? In this paper, three different methods are used and the performance of the three methods is compared. Methods: Autoregressive integrated moving average(ARIMA), support vector machine(SVM) and long short-term memory(LSTM) recurrent neural network were adopted and compared. ARIMA was implemented by python with the help of statsmodels. SVM was accomplished by matlab with libSVM library. LSTM was designed by ourselves with Keras, a deep learning library. To tackle the problem of overfitting caused by limited training samples, we adopted dropout and regularization strategies in our LSTM model. Experimental data were obtained from the monthly incidence and cases number of hepatitis E from January 2005 to December 2017 in Shandong province, China. We selected data from July 2015 to December 2017 to validate the models, and the rest was taken as training set. Three metrics were applied to compare the performance of models, including root mean square error(RMSE), mean absolute percentage error(MAPE) and mean absolute error(MAE). Results: By analyzing data, we took ARIMA(1, 1, 1), ARIMA(3, 1, 2) as monthly incidence prediction model and cases number prediction model, respectively. Cross-validation and grid search were used to optimize parameters of SVM. Penalty coefficient C and kernel function parameter g were set 8, 0.125 for incidence prediction, and 22, 0.01 for cases number prediction. LSTM has 4 nodes. Dropout and L2 regularization parameters were set 0.15, 0.001, respectively. By the metrics of RMSE, we obtained 0.022, 0.0204, 0.01 for incidence prediction, using ARIMA, SVM and LSTM. And we obtained 22.25, 20.0368, 11.75 for cases number prediction, using three models. For MAPE metrics, the results were 23.5%, 21.7%, 15.08%, and 23.6%, 21.44%, 13.6%, for incidence prediction and cases number prediction, respectively. For MAE metrics, the results were 0.018, 0.0167, 0.011 and 18.003, 16.5815, 9.984, for incidence prediction and cases number prediction, respectively. Conclusions: Comparing ARIMA, SVM and LSTM, we found that nonlinear models(SVM, LSTM) outperform linear models(ARIMA). LSTM obtained the best performance in all three metrics of RSME, MAPE, MAE. Hence, LSTM is the most suitable for predicting hepatitis E monthly incidence and cases number. [ABSTRACT FROM AUTHOR]

Bombyx mori nucleopolyhedrovirus (BmNPV) is one of the most serious pathogens in sericulture and causes huge economic loss annually. The roles of N6-methyladenosine (m6A) modification in silkworms following BmNPV infection are currently unclear. Here, methylated RNA immunoprecipitation with next-generation sequencing were applied to investigate the m6A profiles in silkworm midgut following BmNPV infection. A total of 9144 and 7384 m6A peaks were identified from the BmNPV-infected (TEST) and uninfected silkworm midguts (CON), respectively, which were distributed predominantly near stop codons. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of common m6A peaks in nuclear genes revealed that these m6A-related transcripts were associated with crucial signaling pathways. Comparative transcriptome analysis showed that 1221 differential expressed m6A peaks were identified between TEST and CON, indicating that m6A modification is regulated following BmNPV infection. GO and KEGG pathway analysis of the differentially expressed m6A peaks showed their association with signal transduction, translation, and degradation. To understand further the effect of the m6A machinery on virus infection, expression levels of m6A-related genes were altered in silencing and overexpression experiments. Expression of viral structural protein VP39 was increased in BmN cells by siRNA-mediated depletion of methyltransferase-like (METTL) enzyme genes (BmMETTL3, BmMETTL14) and cytoplasmic YTH-domain family 3 (BmYTHDF3), while the reverse results were found after overexpression of the m6A-related enzymes in BmN cells. Overall, m6A modification might be a novel epigenetic mechanism that regulation BmNPV infection and interference with this mechanism may provide a novel antiviral strategy for preventing BmNPV disease. [ABSTRACT FROM AUTHOR]

Background: Hepatitis B vaccine is an effective measure to prevent hepatitis B virus infection. Whether chronic hepatitis C virus (HCV) infection decreases humoral and cell-mediated immunity responses to hepatitis B vaccination is still controversial.Methods: Patients with chronic HCV infection who were not in treatment and healthy controls, matched at a 1:2 ratio for community, sex, and age (within 5 years), were identified from a community-based screening. All participants received 3 doses of hepatitis B vaccine. Antibody to hepatitis B surface antigen was tested 1 month after the third vaccine dose and was compared between 2 groups. Spot-forming cells (SFCs) of interferon γ and interleukin 2, 4, 5, and 6 were counted by means of enzyme-linked immunospot, and SFC counts were compared between the 2 groups.Results: The rates of nonresponse and low, normal, and high response were 3.80%, 10.13%, 45.57%, and 40.50% respectively, in the HCV group, and the corresponding rates in the healthy control group were 1.26%, 10.13%, 39.24%, and 49.37% (all P > .05). There were no significant differences in SFC counts between the 2 groups for interferon γ or interleukin 2, 4, or 5 (all P > .05).Conclusions: This study provided preliminary evidence of the good immunogenicity and safety of hepatitis B vaccination among patients in China with chronic hepatitis C who are not in treatment.Clinical Trials Registration: NCT 02898922. [ABSTRACT FROM AUTHOR]

Hepatitis E vaccine was available in China in 2012, but the priority population for immunization is not clear. In 2013, a hepatitis E outbreak occurred in a company of Shandong province, China where most employees moved from other provinces and dined at the company’s cafeteria. A total of fourteen (19%, 14/73) case-patients were identified, and three of them had symptomatic infection with one death. The proportion of symptomatic infection was much higher among those aged ⩾50 years than those aged <50 years (2/2 vs. 1/12, P = 0.03), and higher in males than females (3/8 vs. 0/6, P = 0.21). Food in the company’s cafeteria might be the possible source of the outbreak. The findings from this outbreak investigation indicate that individuals aged ⩾50 years, particularly males, might be the population of top priority for hepatitis E vaccination in China. [ABSTRACT FROM AUTHOR]

Spontaneous cell-cell fusion has been recognized to be an important mechanism for tissue and organ development and repair. In cancer, cell fusion is critically involved in tumourigenesis, metastasis and drug resistance, as illustrated by in vitro experiments. However, there has been no direct detection of tumour cell fusion or hybridization in an in vivo tumour environment, and the features of hybridized cells under selective pressures, such as chemotherapy, are unknown. Here, we expressed two fluorescent marker proteins in the human breast cancer cell line SKBR3 to detect tumour cell hybridization in vivo and performed a xenograft chemotherapy experiment in mice to evaluate the chemotherapeutic response of the hybrids. The mice treated by epirubicin showed that chemotherapy promoted tumour cell hybridization in vivo, which elicited the production of more hybrids in the outer section of the tumour. These results provide the first in vivo evidence of tumour cell fusion and indicate that chemotherapy may contribute to a poor prognosis by enriching for fused cells, which are more malignant. It is therefore necessary to reassess chemotherapy strategies. [ABSTRACT FROM AUTHOR]

Abstract: Background: It is generally accepted that different high-density lipoprotein (HDL) subclasses have distinct but interrelated metabolic functions. HDL is known to directly influence the atherogenic process and changes in HDL subclasses distribution may be related to the incidence and prevalence of atherosclerosis. Methods: Apo-AI contents(mg/l) of plasma HDL subclasses were determined by 2-dimensional gel electrophoresis coupled with immunodetection for apo-AI. Four hundred forty-two Chinese adults subjects aged 33 to 78 years were assigned to different groups according to the third Report of NCEP (ATP III) guidelines. The subjects were first divided into 2 groups, normal and high TG, then further classified by plasma TC, HDL-C and LDL-C concentrations. The subjects were also divided into TC desirable and TC high groups. Results: Apo-A contents of preβ1-HDL were higher while HDL2b were lower in high TG subjects vs. the corresponding normal TG subjects according to plasma TC and LDL-C concentrations. With the increase of plasma TC concentrations, apo-AI contents of preβ1-HDL were significantly higher in high TC subgroup vs. TC desirable subgroup in normal TG subjects. With the decrease of HDL-C concentrations, apo-AI contents of HDL2b tended to decrease in normal TG subjects. And, with the increases of LDL-C concentration, in normal TG subjects, apo-AI contents of preβ1-HDL and HDL3b were significantly higher and those of HDL2b were significantly lower in very high LDL-C subgroup vs. LDL-C optimal subgroup. On the other hand, apo-AI contents of preβ1-HDL and HDL3a were significantly higher, while HDL2a and HDL2b were significantly lower in high TG and very high TG subgroup vs. normal TG subgroup within either TC desirable or TC high subjects. In a multivariate linear regression model, TG and TC concentrations were all associated independently and positively with high preβ1-HDL; however, HDL-C were inversely associated with high preβ1-HDL. And TG and TC concentrations were all associated independently and negetively with low HDL2b, but HDL-C and apo-AI were positively associated with low HDL2b. Conclusions: With the increase of plasma TG, TC, LDL-C or the decrease of plasma HDL-C concentrations, there was a general shift toward smaller-sized HDL, which, in turn, indicates that reverse cholesterol transport might be weakened and HDL maturation might be abnormal. Plasma TG concentration is a more important factor than TC concentration on the changes of HDL subclass distribution. Moreover, when TG is normal and HDL-C decreased, large-size HDL particles tended to decrease. [Copyright &y& Elsevier]