Modification of polyelectrolyte multilayer coatings using nanoparticles to optimize adhesion and proliferation of different cell types

Adapting characteristics of biomaterials specifically for in vitro and in vivo applications is becoming increasingly important in order to control interactions between material and biological systems. These complex interactions are influenced by surface properties like chemical composition, charge, mechanical and topographic attributes. In many cases it is not useful or even not possible to alter the base material but changing surface, to improve biocompatibility or to make surfaces bioactive, may be achieved by thin coatings. An already established method is the coating with polyelectrolyte multilayers (PEM). To adjust adhesion, proliferation and improve vitality of certain cell types, we modified the roughness of PEM coatings. We included different types nanoparticles (NP’s) in different concentrations into PEM coatings for controlling surface roughness. Surface properties were characterized and the reaction of 3 different cell types on these coatings was tested

Infection, dissemination and transmission rates for <i>Ae. albopictus</i> orally fed with ZIKV and held at 29°C at various days post-infection.

<p>MG = midgut; SG = salivary gland.</p

Additional file 4: Figure S2. of SYBR green-based one step quantitative real-time polymerase chain reaction assay for the detection of Zika virus in field-caught mosquitoes

Melting peak analysis for the rRT-PCR assay performance in field-caught ZIKV-infected mosquitoes. The evaluation is based on the primer combination F2 + R3. The melting peak for ZIKV infected mosquitoes (1–7) and ZIKV non-infected mosquito species (8–14) falls within the same range as the positive control (ATCC® VR-84). (TIFF 679 kb

Additional file 3: Figure S1. of SYBR green-based one step quantitative real-time polymerase chain reaction assay for the detection of Zika virus in field-caught mosquitoes

Melting curve analysis demonstrating the non-specific amplification by primer combinations F + R3, F + R4 and F3 + R4 in the presence of mosquito-derived RNA and specificity of F + R3 in a panel of flavivirus and alphavirus RNA. a. Melting peak analysis for the F + R4 primer pair b. Melting peak analysis for the F3 + R4 primer pair c. Melting peak analysis for the F + R3 primer pair. d. Melting peak analysis for the F + R3 primer pairs within a panel of flavivirus and alphavirus RNA. Abbreviation: NTC, Negative control. (TIFF 2225 kb

Multivariate logistic regression of dengue fever versus chikungunya infection (Table 1a); and dengue hemorrhagic fever versus chikungunya (Table 1b) at presentation among in-patients Tan Tock Seng Hospital, Singapore.

<p>Estimates are derived using Firth's modified score procedure, and confidence intervals using profile penalised likelihoods, as described in the text. Adjusted odds ratios (aOR) are in favour of chikungunya infection: variables associated with chikungunya are indicated in italic type.</p

Sensitivity (sens.), specificity (spec.), positive predictive value (PPV) and area under the receiver operating curve (AUC) for decision tree models to discriminate between dengue fever (DF) or dengue hemorrhagic fever (DHF) versus chikungunya, using data at presentation.

<p>Sensitivity (sens.), specificity (spec.), positive predictive value (PPV) and area under the receiver operating curve (AUC) for decision tree models to discriminate between dengue fever (DF) or dengue hemorrhagic fever (DHF) versus chikungunya, using data at presentation.</p

Sero-Prevalence and Cross-Reactivity of Chikungunya Virus Specific Anti-E2EP3 Antibodies in Arbovirus-Infected Patients

<div><p>Chikungunya virus (CHIKV) and clinically-related arboviruses cause large epidemics with serious economic and social impact. As clinical symptoms of CHIKV infections are similar to several flavivirus infections, good detection methods to identify CHIKV infection are desired for improved treatment and clinical management. The strength of anti-E2EP3 antibody responses was explored in a longitudinal study on 38 CHIKV-infected patients. We compared their anti-E2EP3 responses with those of patients infected with non-CHIKV alphaviruses, or flaviviruses. E2EP3 cross-reactive samples from patients infected with non-CHIKV viruses were further analyzed with an <i>in vitro</i> CHIKV neutralization assay. CHIKV-specific anti-E2EP3 antibody responses were detected in 72% to 100% of patients. Serum samples from patients infected with other non-CHIKV alphaviruses were cross-reactive to E2EP3. Interestingly, some of these antibodies demonstrated clearly <i>in vitro</i> CHIKV neutralizing activity. Contrastingly, serum samples from flaviviruses-infected patients showed a low level of cross-reactivity against E2EP3. Using CHIKV E2EP3 as a serology marker not only allows early detection of CHIKV specific antibodies, but would also allow the differentiation between CHIKV infections and flavivirus infections with 93% accuracy, thereby allowing precise acute febrile diagnosis and improving clinical management in regions newly suffering from CHIKV outbreaks including the Americas.</p></div

Multivariate logistic regression of dengue fever versus chikungunya infection (Table 2a); and dengue hemorrhagic fever versus chikungunya (Table 2b) during entire hospital stay among inpatients at Tan Tock Seng Hospital, Singapore, 2006–8.

<p>Estimates are derived using Firth's modified score procedure, and confidence intervals using profile penalised likelihoods, as described in the text. Adjusted odds ratios (aOR) are in favour of chikungunya infection: variables associated with chikungunya are indicated in italic type.</p

Time course analysis of selected variables.

<p>Analysis shows platelet counts (A), serum hematocrit (B), leukocyte (C), and temperature (D) for dengue fever (DF), dengue hemorrhagic fever (DHF) and chikungunya. Individual data are indicated in semi-transparent red (chikungunya), black (DF), and blue(DHF) lines. Overall means are indicated as solid lines, with 95% credible intervals as dashed lines. The bar on X-axis indicates in black days with a ‘significant’ difference (defined as 95% credible interval for the difference between the two disease means not crossing zero) between chikungunya and DF, and the blue bar between chikungunya and DHF.</p

Cross-reactivity of anti-alphaviruses and anti-flaviviruses antibodies with CHIKV E2EP3.

<p>Patient serum samples caused by non-CHIKV alphaviruses infections (n = 19) and flaviviruses infections (n = 60) were screened for cross-reactivity against CHIKV E2EP3 by peptide-based ELISA at a dilution of 1∶4000. <i>A,</i> Pie-chart shows the percentage of non-CHIKV alphaviruses-infected patients samples with positive or negative anti-E2EP3 antibody response. <i>B,</i> Pie-chart shows the percentage of flaviviruses-infected patient samples with positive or negative anti-E2EP3 antibody response. <i>C - D,</i> Pie-chart shows the percentage of DENV-infected and non-DENV flaviviruses-infected patient samples with positive or negative anti-E2EP3 IgG antibody response respectively. <i>E,</i> Detection of CHIKV E2EP3 by serum samples of unknown infections. Serum samples (n = 71) of febrile patients from unknown cause of infections were screened by peptide-based ELISA at a dilution of 1∶4000. Pie-chart shows the percentage of patients' samples with positive or negative anti-E2EP3 antibody response. <i>F,</i> Bar-chart shows the number of non-CHIKV alphaviruses-infected, E2EP3 cross-reactive samples with and without CHIKV neutralizing activity against the two CHIKV isolates (CHIKV (A226) and CHIKV (A226V)).</p