Informative Motif Detection Using Data Mining

Abstract: Motif finding in biological sequences is a fundamental problem in computational biology with important applications in understanding gene regulation, protein family identification and determination of functionally and structurally important identities. The large amounts of biological data let us solve the problem of discovering patterns in biological sequences computationally. In this research, we have developed an approach using a method of data mining to detect frequent residue informative motifs that are high in information content. The proposed approach modifies an existing method based on Apriori algorithm by using the Frequent Pattern tree (FP-tree) algorithm of data mining method. This method can efficiently detect novel motifs in biological sequences based on information content of the motifs and shows better performance than the existing method. Experiments on real biological sequence data sets demonstrate the effectiveness of the method

Anisotropic nonlinear elasticity in a spherical bead pack: influence of the fabric anisotropy

Stress-strain measurements and ultrasound propagation experiments in glass bead packs have been simultaneously conducted to characterize the stress-induced anisotropy under uniaxial loading. These measurements, realized respectively with finite and incremental deformations of the granular assembly, are analyzed within the framework of the effective medium theory based on the Hertz-Mindlin contact theory. Our work shows that both compressional and shear wave velocities and consequently the incremental elastic moduli agree fairly well with the effective medium model by Johnson et al. [J. Appl. Mech. 65, 380 (1998)], but the anisotropic stress ratio resulting from finite deformation does not at all. As indicated by numerical simulations, the discrepancy may arise from the fact that the model doesn't properly allow the grains to relax from the affine motion approximation. Here we find that the interaction nature at the grain contact could also play a crucial role for the relevant prediction by the model; indeed, such discrepancy can be significantly reduced if the frictional resistance between grains is removed. Another main experimental finding is the influence of the inherent anisotropy of granular packs, realized by different protocols of the sample preparation. Our results reveal that compressional waves are more sensitive to the stress-induced anisotropy, whereas the shear waves are more sensitive to the fabric anisotropy, not being accounted in analytical effective medium models.Comment: 9 pages, 8 figure

Considering Respiratory Tract Infections and Antimicrobial Sensitivity: An Exploratory Analysis

This study was conducted to observe the sensitivity and resistance of status of antibiotics for respiratory tract infection (RTI). Throat swab culture and sensitivity report of 383 patients revealed sensitivity profiles were observed with amoxycillin (7.9%), penicillin (33.7%), ampicillin (36.6%), co-trimoxazole (46.5%), azithromycin (53.5%), erythromycin (57.4%), cephalexin (69.3%), gentamycin (78.2%), ciprofloxacin (80.2%), cephradine (81.2%), ceftazidime (93.1%), ceftriaxone (93.1%). Sensitivity to cefuroxime was reported 93.1% cases. Resistance was found with amoxycillin (90.1%), ampicillin (64.1%), penicillin (61.4%), co-trimoxazole (43.6%), erythromycin (39.6%), and azithromycin (34.7%). Cefuroxime demonstrates high level of sensitivity than other antibiotics and supports its consideration with patients with upper RTI

Impact of the Coverage of Aptamers on a Nanoparticle on the Binding Equilibrium and Kinetics between Aptamer and Protein

Knowledge of the interaction between aptamer and protein is integral to the design and development of aptamer-based biosensors. Nanoparticles functionalized with aptamers are commonly used in these kinds of sensors. As such, studies into how the number of aptamers on the nanoparticle surface influence both kinetics and thermodynamics of the binding interaction are required. In this study, aptamers specific for interferon gamma (IFN-γ) were immobilized on the surface of gold nanoparticles (AuNPs), and the effect of surface coverage of aptamer on the binding interaction with its target was investigated using fluorescence spectroscopy. The number of aptamers were adjusted from an average of 9.6 to 258 per particle. The binding isotherm between AuNPs-aptamer conjugate and protein was modeled with the Hill-Langmuir equation, and the determined equilibrium dissociation constant (K′D) decreased 10-fold when increasing the coverage of aptamer. The kinetics of the reaction as a function of coverage of aptamer were also investigated, including the association rate constant (kon) and the dissociation rate constant (koff). The AuNPs-aptamer conjugate with 258 aptamers per particle had the highest kon, while the koff was similar for AuNPs-aptamer conjugates with different surface coverages. Therefore, the surface coverage of aptamers on AuNPs affects both the thermodynamics and the kinetics of the binding. The AuNPs-aptamer conjugate with the highest surface coverage is the most favorable in biosensors considering the limit of detection, sensitivity, and response time of the assay. These findings deepen our understanding of the interaction between aptamer and target protein on the particle surface, which is important to both improve the scientific design and increase the application of aptamer-nanoparticle based biosensor

Mosquitoes reared in distinct insectaries within an institution in close spatial proximity possess significantly divergent microbiomes

The microbiome affects important aspects of mosquito biology and differences in microbial composition can affect the outcomes of laboratory studies. To determine how the biotic and abiotic conditions in an insectary affect the composition of the bacterial microbiome of mosquitoes we reared mosquitoes from a single cohort of eggs from one genetically homogeneous inbred Aedes aegypti colony, which were split into three batches, and transferred to each of three different insectaries located within the Liverpool School of Tropical Medicine. Using three replicate trays per insectary, we assessed and compared the bacterial microbiome composition as mosquitoes developed from these eggs. We also characterised the microbiome of the mosquitoes' food sources, measured environmental conditions over time in each climate-controlled insectary, and recorded development and survival of mosquitoes. While mosquito development was overall similar between all three insectaries, we saw differences in microbiome composition between mosquitoes from each insectary. Furthermore, bacterial input via food sources, potentially followed by selective pressure of temperature stability and range, did affect the microbiome composition. At both adult and larval stages, specific members of the mosquito microbiome were associated with particular insectaries; and the insectary with less stable and cooler conditions resulted in slower pupation rate and higher diversity of the larval microbiome. Tray and cage effects were also seen in all insectaries, with different bacterial taxa implicated between insectaries. These results highlight the necessity of considering the variability and effects of different microbiome composition even in experiments carried out in a laboratory environment starting with eggs from one batch; and highlights the impact of even minor inconsistencies in rearing conditions due to variation of temperature and humidity.</p

Validating child vaccination status in a demographic surveillance system using data from a clinical cohort study: evidence from rural South Africa

&lt;p&gt;&lt;b&gt;Background:&lt;/b&gt; Childhood vaccination coverage can be estimated from a range of sources. This study aims to validate vaccination data from a longitudinal population-based demographic surveillance system (DSS) against data from a clinical cohort study.&lt;/p&gt; &lt;p&gt;&lt;b&gt;Methods:&lt;/b&gt; The sample includes 821 children in the Vertical Transmission cohort Study (VTS), who were born between December 2001 and April 2005, and were matched to the Africa Centre DSS, in northern KwaZulu-Natal. Vaccination information in the surveillance was collected retrospectively, using standardized questionnaires during bi-annual household visits, when the child was 12 to 23 months of age. DSS vaccination information was based on extraction from a vaccination card or, if the card was not available, on maternal recall. In the VTS, vaccination data was collected at scheduled maternal and child clinic visits when a study nurse administered child vaccinations. We estimated the sensitivity of the surveillance in detecting vaccinations conducted as part of the VTS during these clinic visits.&lt;/p&gt; &lt;p&gt;&lt;b&gt;Results:&lt;/b&gt; Vaccination data in matched children in the DSS was based on the vaccination card in about two-thirds of the cases and on maternal recall in about one-third. The sensitivity of the vaccination variables in the surveillance was high for all vaccines based on either information from a South African Road-to-Health (RTH) card (0.94-0.97) or maternal recall (0.94-0.98). Addition of maternal recall to the RTH card information had little effect on the sensitivity of the surveillance variable (0.95-0.97). The estimates of sensitivity did not vary significantly, when we stratified the analyses by maternal antenatal HIV status. Addition of maternal recall of vaccination status of the child to the RTH card information significantly increased the proportion of children known to be vaccinated across all vaccines in the DSS.&lt;/p&gt; &lt;p&gt;&lt;b&gt;Conclusion:&lt;/b&gt; Maternal recall performs well in identifying vaccinated children aged 12-23 months (both in HIV-infected and HIV-uninfected mothers), with sensitivity similar to information extracted from vaccination cards. Information based on both maternal recall and vaccination cards should be used if the aim is to use surveillance data to identify children who received a vaccination.&lt;/p&gt