3D-QSAR studija afiniteta vezanja na receptor za (R,S)-2-amino-3-(3-hidroksi-5-metilizoksazol-4-il)-propansku kiselinu

An approach for binding affinity evaluation is suggested and exemplified using a set of triazolo [1,5-a] quinoxaline for the (R,S)-2-amino-3-(3-hydroxy-5-methylisoxazol-4-yl)-propionic acid (AMPA) receptor. Biological activity toward the AMPA receptor (expressed as -log IC5O) was taken as a dependent variable for building Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) models. The resulting models show the ways of increasing the binding affinity to the AMPA receptor as a potential target for epilepsy. The statistically significant results show that the cross-validated r2CV value (0.766) for the CoMFA model is greater than (0.758) for the CoMSIA model. The non-cross validated run giving the coefficient of determination r2 values of 0.944 and 0.919 for CoMFA and CoMSIA, respectively, provided good correlation between the observed and computed affinities of the training set compounds. The resulting CoMFA and CoMSIA models indicate that steric, electrostatic, hydrophobic (lipophilic), hydrogen bond donor and acceptor substituents play a significant role in increasing the binding affinity and selectivity of the compounds toward the AMPA receptor.U radu je vrednovan afinitet vezanja serije triazolo[1,5-a]kinoksalina na receptor za (R,S)-2-amino-3-(3-hidroksi-5-metilizoksazol-4-il)-propansku kiselinu (AMPA). Djelovanje na AMPA receptor (izraženo kao log IC5O) uzeta je kao zavisna varijabla u modelima usporedne analize molekulskih polja (Comparative Molecular Field Analysis, CoMFA) i usporedne analize molekulske sličnosti (Comparative Molecular Similarity Indices Analysis, CoMSIA). Ti modeli pokazuju kako povećati afinitet vezanja na AMPA receptor, što može biti korisno u terapiji epilepsije. Statistički značajni rezultati ukazuju da je križno validirana r2CV vrijednost za CoMFA model (0,766) veća nego za CoMSIA model (0,758). Koeficijenti r2 za CoMFA model (0,944) i CoMSIA (0,919) ukazuju na dobru korelaciju između izračunatih i eksperimentalno određanih afiniteta vezanja proučavane serije spojeva. Prema oba modela za povećanje afiniteta vezanja i selektivnost spojeva za AMPA receptor značajna su sterička, elektrostatska, hidrofobna (lipofilni) svojstva, te sposobnost stvaranja vodikovih veza

Network model of immune responses reveals key effectors to single and co-infection dynamics by a respiratory bacterium and a gastrointestinal helminth

Co-infections alter the host immune response but how the systemic and local processes at the site of infection interact is still unclear. The majority of studies on co-infections concentrate on one of the infecting species, an immune function or group of cells and often focus on the initial phase of the infection. Here, we used a combination of experiments and mathematical modelling to investigate the network of immune responses against single and co-infections with the respiratory bacterium Bordetella bronchiseptica and the gastrointestinal helminth Trichostrongylus retortaeformis. Our goal was to identify representative mediators and functions that could capture the essence of the host immune response as a whole, and to assess how their relative contribution dynamically changed over time and between single and co-infected individuals. Network-based discrete dynamic models of single infections were built using current knowledge of bacterial and helminth immunology; the two single infection models were combined into a co-infection model that was then verified by our empirical findings. Simulations showed that a T helper cell mediated antibody and neutrophil response led to phagocytosis and clearance of B. bronchiseptica from the lungs. This was consistent in single and co-infection with no significant delay induced by the helminth. In contrast, T. retortaeformis intensity decreased faster when co-infected with the bacterium. Simulations suggested that the robust recruitment of neutrophils in the co-infection, added to the activation of IgG and eosinophil driven reduction of larvae, which also played an important role in single infection, contributed to this fast clearance. Perturbation analysis of the models, through the knockout of individual nodes (immune cells), identified the cells critical to parasite persistence and clearance both in single and co-infections. Our integrated approach captured the within-host immuno-dynamics of bacteria-helminth infection and identified key components that can be crucial for explaining individual variability between single and co-infections in natural populations

Systematic literature review of prediction techniques to identify work skillset

A mismatch of skillsets is a main cause to the unemployment in Malaysia. It is a situation where the level and work skillset that are available do not match the market demands and the individual does not know how to identify the skills that they have. To deal with this problem, prediction techniques is used to assist in identifying work-appropriate skills for individual. Thus, a systematic literature review (SLR) on predicting work skillsets using prediction techniques is proposed. The aim of this study is to give an overview on the prediction techniques that have been used to predict work skillset and the accuracy of the techniques. We use SLR to identify 383 prediction techniques studies for identifying skills published from 2014 to 2019. As a result, 9 studies report adequate information and methodology according to our criteria and apply. From the studies, classification techniques are used for predicting work skillset. The algorithms used is Random Forest with precision is 99%. From this study, a future study will be conducted by developing a prediction model to help identifying appropriate work skillsets to meet current needs and identifying the levels of skills they have. The significant of this study is the researchers are able to understand deeply about the prediction techniques used to identify work skillset and the accuracy of the techniques used

Maternal outcomes in subsequent delivery after previous obstetric anal sphincter injury (OASI): a multi-centre retrospective cohort study.

INTRODUCTION AND HYPOTHESIS: Women with a history of obstetric anal sphincter injury (OASI) are at increased risk of recurrence (rOASI) at subsequent delivery; however, evidence regarding the factors influencing this risk is limited. Furthermore, little is known about what factors influence the decision to alternatively deliver by elective caesarean section (ELLSCS). METHODS: Retrospective univariate and multivariate logistic regression analysis of prospectively collected data from four NHS electronic maternity databases including primiparous women sustaining OASIS during a singleton, term, cephalic, vaginal delivery between 2004 and 2015, who had a subsequent delivery. RESULTS: Two thousand two hundred seventy-two women met the criteria; 10.2% delivering vaginally had a repeat OASI and 59.4% had a second-degree tear. Women having an ELLSCS were more likely to be Caucasian, older, have previously had an operative vaginal delivery (OVD) and have a more severe degree of OASI. Positive predictors for rOASI were increased birth weight and maternal age at both index and subsequent deliveries, a more severe degree of initial OASI and Asian ethnicity. The overall mediolateral episiotomy (MLE) rate was 15.6%; 77.2% of those who had an episiotomy sustained no spontaneous perineal trauma. Only 4.4% of women with a rOASI had an MLE, whilst the MLE rate was 16.9% in those without a recurrence (p  4 kg increased the risk 2.5 fold. CONCLUSIONS: Women with previous OASIS are at an increased risk of recurrence. A more liberal use of MLE during subsequent vaginal delivery could significantly reduce the risk of recurrence

Reconstruction of regulatory networks through temporal enrichment profiling and its application to H1N1 influenza viral infection

BACKGROUND: H1N1 influenza viruses were responsible for the 1918 pandemic that caused millions of deaths worldwide and the 2009 pandemic that caused approximately twenty thousand deaths. The cellular response to such virus infections involves extensive genetic reprogramming resulting in an antiviral state that is critical to infection control. Identifying the underlying transcriptional network driving these changes, and how this program is altered by virally-encoded immune antagonists, is a fundamental challenge in systems immunology. RESULTS: Genome-wide gene expression patterns were measured in human monocyte-derived dendritic cells (DCs) infected in vitro with seasonal H1N1 influenza A/New Caledonia/20/1999. To provide a mechanistic explanation for the timing of gene expression changes over the first 12 hours post-infection, we developed a statistically rigorous enrichment approach integrating genome-wide expression kinetics and time-dependent promoter analysis. Our approach, TIme-Dependent Activity Linker (TIDAL), generates a regulatory network that connects transcription factors associated with each temporal phase of the response into a coherent linked cascade. TIDAL infers 12 transcription factors and 32 regulatory connections that drive the antiviral response to influenza. To demonstrate the generality of this approach, TIDAL was also used to generate a network for the DC response to measles infection. The software implementation of TIDAL is freely available at http://tsb.mssm.edu/primeportal/?q=tidal_prog. CONCLUSIONS: We apply TIDAL to reconstruct the transcriptional programs activated in monocyte-derived human dendritic cells in response to influenza and measles infections. The application of this time-centric network reconstruction method in each case produces a single transcriptional cascade that recapitulates the known biology of the response with high precision and recall, in addition to identifying potentially novel antiviral factors. The ability to reconstruct antiviral networks with TIDAL enables comparative analysis of antiviral responses, such as the differences between pandemic and seasonal influenza infections

Data mining techniques for predicting acute kidney injury after elective cardiac surgery

status: publishe