CD36 Participates in PrP106–126-Induced Activation of Microglia

Microglial activation is a characteristic feature of the pathogenesis of prion diseases. The molecular mechanisms that underlie prion-induced microglial activation are not very well understood. In the present study, we investigated the role of the class B scavenger receptor CD36 in microglial activation induced by neurotoxic prion protein (PrP) fragment 106–126 (PrP106–126). We first examined the time course of CD36 mRNA expression upon exposure to PrP106–126 in BV2 microglia. We then analyzed different parameters of microglial activation in PrP106–126-treated cells in the presence or not of anti-CD36 monoclonal antibody (mAb). The cells were first incubated for 1 h with CD36 monoclonal antibody to block the CD36 receptor, and were then treated with neurotoxic prion peptides PrP106–126. The results showed that PrP106–126 treatment led to a rapid yet transitory increase in the mRNA expression of CD36, upregulated mRNA and protein levels of proinflammatory cytokines (IL-1β, IL-6 and TNF-α), increased iNOS expression and nitric oxide (NO) production, stimulated the activation of NF-κB and caspase-1, and elevated Fyn activity. The blockade of CD36 had no effect on PrP106–126-stimulated NF-κB activation and TNF-α protein release, abrogated the PrP106–126-induced iNOS stimulation, downregulated IL-1β and IL-6 expression at both mRNA and protein levels as well as TNF-α mRNA expression, decreased NO production and Fyn phosphorylation, reduced caspase-1 cleavage induced by moderate PrP106–126 –treatment, but had no effect on caspase-1 activation after treatment with a high concentration of PrP106–126. Together, these results suggest that CD36 is involved in PrP106–126-induced microglial activation and that the participation of CD36 in the interaction between PrP106–126 and microglia may be mediated by Src tyrosine kinases. Our findings provide new insights into the mechanisms underlying the activation of microglia by neurotoxic prion peptides and open perspectives for new therapeutic strategies for prion diseases by modulation of CD36 signaling

BCG vaccination strategies against tuberculosis: updates and perspectives

Bacillus Calmette-Guérin (BCG) is the only licensed vaccine against tuberculosis (TB). However, BCG has variable efficacy and cannot completely prevent TB infection and transmission. Therefore, the worldwide prevalence of TB calls for urgent development of a more effective TB vaccine. In the absence of other approved vaccines, it is also necessary to improve the efficacy of BCG itself. Intravenous (IV) BCG administration and BCG revaccination strategies have recently shown promising results for clinical usage. Therefore, it is necessary for us to revisit the BCG vaccination strategies and summarize the current research updates related to BCG vaccination. This literature review provides an updated overview and perspectives of the immunization strategies against TB using BCG, which may inspire the following research on TB vaccine development

Traffic Volatility Forecasting Using an Omnibus Family GARCH Modeling Framework

Traffic volatility modeling has been highly valued in recent years because of its advantages in describing the uncertainty of traffic flow during the short-term forecasting process. A few generalized autoregressive conditional heteroscedastic (GARCH) models have been developed to capture and hence forecast the volatility of traffic flow. Although these models have been confirmed to be capable of producing more reliable forecasts than traditional point forecasting models, the more or less imposed restrictions on parameter estimations may make the asymmetric property of traffic volatility be not or insufficiently considered. Furthermore, the performance of the models has not been fully evaluated and compared in the traffic forecasting context, rendering the choice of the models dilemmatic for traffic volatility modeling. In this study, an omnibus traffic volatility forecasting framework is proposed, where various traffic volatility models with symmetric and asymmetric properties can be developed in a unifying way by fixing or flexibly estimating three key parameters, namely the Box-Cox transformation coefficient λ, the shift factor b, and the rotation factor c. Extensive traffic speed datasets collected from urban roads of Kunshan city, China, and from freeway segments of the San Diego Region, USA, were used to evaluate the proposed framework and develop traffic volatility forecasting models in a number of case studies. The models include the standard GARCH, the threshold GARCH (TGARCH), the nonlinear ARCH (NGARCH), the nonlinear-asymmetric GARCH (NAGARCH), the Glosten–Jagannathan–Runkle GARCH (GJR-GARCH), and the family GARCH (FGARCH). The mean forecasting performance of the models was measured with mean absolute error (MAE) and mean absolute percentage error (MAPE), while the volatility forecasting performance of the models was measured with volatility mean absolute error (VMAE), directional accuracy (DA), kickoff percentage (KP), and average confidence length (ACL). Experimental results demonstrate the effectiveness and flexibility of the proposed framework and provide insights into how to develop and select proper traffic volatility forecasting models in different situations

Complexity of conditional colorability of graphs

For positive integers $k$ and $r$, a conditional $(k,r)$-coloring of a graph $G$ is a proper $k$-coloring of the vertices of $G$ such that every vertex $v$ of degree $d(v)$ in $G$ is adjacent to vertices with at least $\min\{r,d(v)\}$ different colors. The smallest integer $k$ for which a graph $G$ has a conditional $(k,r)$-coloring is called the $r$th-order conditional chromatic number, and is denoted by $X_r(G)$. It is easy to see that conditional coloring is a generalization of traditional vertex coloring (the case $r=1$). In this work, we consider the complexity of the conditional colorability of graphs. Our main result is that conditional (3,2)-colorability remains NP-complete when restricted to planar bipartite graphs with maximum degree at most 3 and arbitrarily high girth. This differs considerably from the well-known result that traditional 3-colorability is polynomially solvable for graphs with maximum degree at most 3. On the other hand we show that (3,2)-colorability is polynomially solvable for graphs with bounded tree-width. We also prove that some other well-known complexity results for traditional coloring still hold for conditional coloring.\ud \u

Performance Analysis of Binary Search Algorithm in RFID

Binary search algorithm (BS) is a kind of important anti-collision algorithm in the Radio Frequency Identification (RFID), is also one of the key technologies which determine whether the information in the tag is identified by the reader-writer fast and reliably. The performance of BS directly affects the quality of service in Internet of Things. This paper adopts an automated formal technology: probabilistic model checking to analyze the performance of BS algorithm formally. Firstly, according to the working principle of BS algorithm, its dynamic behavior is abstracted into a Discrete Time Markov Chains which can describe deterministic, discrete time and the probability selection. And then on the model we calculate the probability of the data sent successfully and the expected time of tags completing the data transmission. Compared to the another typical anti-collision protocol S-ALOHA in RFID, experimental results show that with an increase in the number of tags the BS algorithm has a less space and time consumption, the average number of conflicts increases slower than the S-ALOHA protocol standard, BS algorithm needs fewer expected time to complete the data transmission, and the average speed of the data transmission in BS is as 1.6 times as the S-ALOHA protocol

Defensins: The Case for Their Use against Mycobacterial Infections

Human tuberculosis remains a huge global public health problem with an estimated 1/3rd of the population being infected. Defensins are antibacterial cationic peptides produced by a number of cell types, most notably neutrophil granulocytes and epithelial cells. All three defensin types (α-, β-, and θ-defensins) have antibacterial activities, mainly through bacterial membrane permeabilization. Defensins are effective against Gram-negative and Gram-positive bacteria including mycobacteria and are active both intra- and extracellularly. Mycobacterial resistance has never been demonstrated although the mprF gene encoding resistance in Staphylococcus aureus is present in the Mycobacterium tuberculosis genome. In addition to their antibacterial effect, defensins are chemoattractants for macrophages and neutrophils. There are many cases for their use for therapy or prophylaxis in tuberculosis as well. In conclusion, we propose that there is considerable scope and potential for exploring their use as therapeutic/prophylactic agents and more comprehensive survey of defensins from different species and their bioactivity is timely

Texture Analysis Improves the Value of Pretreatment 18F-FDG PET/CT in Predicting Interim Response of Primary Gastrointestinal Diffuse Large B-Cell Lymphoma

Objectives. To explore the application of pretreatment 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) texture analysis (TA) in predicting the interim response of primary gastrointestinal diffuse large B-cell lymphoma (PGIL-DLBCL). Methods. Pretreatment 18F-FDG PET/CT images of 30 PGIL-DLBCL patients were studied retrospectively. The interim response was evaluated after 3-4 cycles of chemotherapy. The complete response (CR) rates in patients with different clinicopathological characteristics were compared by Fisher’s exact test. The differences in the maximum standard uptake value (SUVmax), metabolic tumor volume (MTV), and texture features between the CR and non-CR groups were compared by the Mann–Whitney U test. Feature selection was performed according to the results of the Mann–Whitney U test and feature categories. The predictive efficacies of the SUVmax, MTV, and the selected texture features were assessed by receiver operating characteristic (ROC) analysis. A prediction probability was generated by binary logistic regression analysis. Results. The SUVmax, MTV, some first-order texture features, volume, and entropy were significantly higher in the non-CR group. The energy was significantly lower in the non-CR group. The SUVmax, volume, and entropy were excellent predictors of the interim response, and the areas under the curves (AUCs) were 0.850, 0.805, and 0.800, respectively. The CR rate was significantly lower in patients with intestinal involvement. The prediction probability generated from the combination of the SUVmax, entropy, volume, and intestinal involvement had a higher AUC (0.915) than all single parameters. Conclusions. TA has potential in improving the value of pretreatment PET/CT in predicting the interim response of PGIL-DLBCL. However, prospective studies with large sample sizes and validation analyses are needed to confirm the current results