Mathematical model to predict drivers' reaction speeds

Mental distractions and physical impairments can increase the risk of accidents by affecting a driver's ability to control the vehicle. In this article, we developed a linear mathematical model that can be used to quantitatively predict drivers' performance over a variety of possible driving conditions. Predictions were not limited only to conditions tested, but also included linear combinations of these tests conditions. Two groups of 12 participants were evaluated using a custom drivers' reaction speed testing device to evaluate the effect of cell phone talking, texting, and a fixed knee brace on the components of drivers' reaction speed. Cognitive reaction time was found to increase by 24% for cell phone talking and 74% for texting. The fixed knee brace increased musculoskeletal reaction time by 24%. These experimental data were used to develop a mathematical model to predict reaction speed for an untested condition, talking on a cell phone with a fixed knee brace. The model was verified by comparing the predicted reaction speed to measured experimental values from an independent test. The model predicted full braking time within 3% of the measured value. Although only a few influential conditions were evaluated, we present a general approach that can be expanded to include other types of distractions, impairments, and environmental conditions.     

Association of the Maternal MTHFR C677T Polymorphism with Susceptibility to Neural Tube Defects in Offsprings: Evidence from 25 Case-Control Studies

Background

Methylenetetrahydrofolate reductase (MTHFR) is a critical enzyme in folate metabolism and is involved in DNA methylation, DNA synthesis, and DNA repair. In addition, it is a possible risk factor in neural tube defects (NTDs). The association of the C677T polymorphism in the MTHFR gene and NTD susceptibility has been widely demonstrated, but the results remain inconclusive. In this study, we performed a meta-analysis with 2429 cases and 3570 controls to investigate the effect of the MTHFR C677T polymorphism on NTDs.

Methods

An electronic search of PubMed and Embase database for papers on the MTHFR C677T polymorphism and NTD risk was performed. All data were analysed with STATA (version 11). Odds ratios (ORs) with 95% confidence intervals (CIs) were estimated to assess the association. Sensitivity analysis, test of heterogeneity, cumulative meta-analysis, and assessment of bias were performed in our meta-analysis.

Results

A significant association between the MTHFR C677T polymorphism and NTD susceptibility was revealed in our meta-analysis ( TT versus CC: OR  = 2.022, 95% CI: 1.508, 2.712; CT+TT versus CC: OR  = 1.303, 95% CI: 1.089, 1.558; TT versus CC+CT: OR  = 1.716, 95% CI: 1.448, 2.033; 2TT+CT versus 2CC+CT: OR  = 1.330, 95% CI: 1.160, 1.525). Moreover, an increased NTD risk was found after stratification of the MTHFR C677T variant data by ethnicity and source of controls.

Conclusion

The results suggested the maternal MTHFR C677T polymorphism is a genetic risk factor for NTDs. Further functional studies to investigate folate-related gene polymorphisms, periconceptional multivitamin supplements, complex interactions, and the development of NTDs are warranted.     

Effect of SNPs on Creatine Kinase Structure and Function: Identifying Potential Molecular Mechanisms for Possible Creatine Kinase Deficiency Diseases

Single-nucleotide polymorphisms (SNPs) are common genetic material changes that often occur naturally. SNPs can cause amino acid replacements that may lead to severe diseases, such as the well-known sickle-cell anemia. We constructed eight SNP mutants of human brain-type creatine kinase (CKB) based on bioinformatics predictions. The biochemical and biophysical characteristics of these SNP mutants were determined and compared to those of the wild-type creatine kinase to explore the potential molecular mechanisms of possible creatine kinase SNP-induced diseases. While the reactivation of six SNP mutants after heat shock dropped more than 45%, only three of them showed notable increases in ANS fluorescence intensity and decreases in catalytic efficiency. Among them, H26Y and P36T bind substrates as well as the wild-type form does, but the melting temperatures (T_m) dropped below body temperature, while the T59I mutant exhibited decreased catalytic activity that was most likely due to the much reduced binding affinity of this mutant for substrates. These findings indicate that SNPs such as H26Y, P36T and T59I have the potential to induce genetic diseases by different mechanisms.     

5-Aza-2′-deoxycytidine Leads to Reduced Embryo Implantation and Reduced Expression of DNA Methyltransferases and Essential Endometrial Genes

Background

The DNA demethylating agent 5-aza-2′-deoxycytidine (5-aza-CdR) incorporates into DNA and decreases DNA methylation, sparking interest in its use as a potential therapeutic agent. We aimed to determine the effects of maternal 5-aza-CdR treatment on embryo implantation in the mouse and to evaluate whether these effects are associated with decreased levels of DNA methyltransferases (Dnmts) and three genes (estrogen receptor α [Esr1], progesterone receptor [Pgr], and homeobox A10 [Hoxa10]) that are vital for control of endometrial changes during implantation.

Methods and Principal Findings

Mice treated with 5-aza-CdR had a dose-dependent decrease in number of implantation sites, with defected endometrial decidualization and stromal cell proliferation. Western blot analysis on pseudo-pregnant day 3 (PD3) showed that 0.1 mg/kg 5-aza-CdR significantly repressed Dnmt3a protein level, and 0.5 mg/kg 5-aza-CdR significantly repressed Dnmt1, Dnmt3a, and Dnmt3b protein levels in the endometrium. On PD5, mice showed significantly decreased Dnmt3a protein level with 0.1 mg/kg 5-aza-CdR, and significantly decreased Dnmt1 and Dnmt3a with 0.5 mg/kg 5-aza-CdR. Immunohistochemical staining showed that 5-aza-CdR repressed DNMT expression in a cell type–specific fashion within the uterus, including decreased expression of Dnmt1 in luminal and/or glandular epithelium and of Dnmt3a and Dnmt3b in stroma. Furthermore, the 5′ flanking regions of the Esr1, Pgr, and Hoxa10 were hypomethylated on PD5. Interestingly, the higher (0.5 mg/kg) dose of 5-aza-CdR decreased protein expression of Esr1, Pgr, and Hoxa10 in the endometrium on PD5 in both methylation-dependent and methylation-independent manners.

Conclusions

The effects of 5-aza-CdR on embryo implantation in mice were associated with altered expression of endometrial Dnmts and genes controlling endometrial changes, suggesting that altered gene methylation, and not cytotoxicity alone, contributes to implantation defects induced by 5-aza-CdR.     

Diversity of Xenorhabdus and Photorhabdus spp. and Their Symbiotic Entomopathogenic Nematodes from Thailand

Xenorhabdus and Photorhabdus spp. are bacterial symbionts of entomopathogenic nematodes (EPNs). In this study, we isolated and characterized Xenorhabdus and Photorhabdus spp. from across Thailand together with their associated nematode symbionts, and characterized their phylogenetic diversity. EPNs were isolated from soil samples using a Galleria-baiting technique. Bacteria from EPNs were cultured and genotyped based on recA sequence. The nematodes were identified based on sequences of 28S rDNA and internal transcribed spacer regions. A total of 795 soil samples were collected from 159 sites in 13 provinces across Thailand. A total of 126 EPNs isolated from samples taken from 10 provinces were positive for Xenorhabdus (n = 69) or Photorhabdus spp. (n = 57). Phylogenetic analysis separated the 69 Xenorhabdus isolates into 4 groups. Groups 1, 2 and 3 consisting of 52, 13 and 1 isolates related to X. stockiae, and group 4 consisting of 3 isolates related to X. miraniensis. The EPN host for isolates related to X. stockiae was S. websteri, and for X. miraniensis was S. khoisanae. The Photorhabdus species were identified as P. luminescens (n = 56) and P. asymbiotica (n = 1). Phylogenenic analysis divided P. luminescens into five groups. Groups 1 and 2 consisted of 45 and 8 isolates defined as subspecies hainanensis and akhurstii, respectively. One isolate was related to hainanensis and akhurstii, two isolates were related to laumondii, and one isolate was the pathogenic species P. asymbiotica subsp. australis. H. indica was the major EPN host for Photorhabdus. This study reveals the genetic diversity of Xenorhabdus and Photorhabdus spp. and describes new associations between EPNs and their bacterial symbionts in Thailand.     

A Fast EM Algorithm for BayesA-Like Prediction of Genomic Breeding Values

Prediction accuracies of estimated breeding values for economically important traits are expected to benefit from genomic information. Single nucleotide polymorphism (SNP) panels used in genomic prediction are increasing in density, but the Markov Chain Monte Carlo (MCMC) estimation of SNP effects can be quite time consuming or slow to converge when a large number of SNPs are fitted simultaneously in a linear mixed model. Here we present an EM algorithm (termed “fastBayesA”) without MCMC. This fastBayesA approach treats the variances of SNP effects as missing data and uses a joint posterior mode of effects compared to the commonly used BayesA which bases predictions on posterior means of effects. In each EM iteration, SNP effects are predicted as a linear combination of best linear unbiased predictions of breeding values from a mixed linear animal model that incorporates a weighted marker-based realized relationship matrix. Method fastBayesA converges after a few iterations to a joint posterior mode of SNP effects under the BayesA model. When applied to simulated quantitative traits with a range of genetic architectures, fastBayesA is shown to predict GEBV as accurately as BayesA but with less computing effort per SNP than BayesA. Method fastBayesA can be used as a computationally efficient substitute for BayesA, especially when an increasing number of markers bring unreasonable computational burden or slow convergence to MCMC approaches.     

Drug discovery prospect from untapped species: indications from approved natural product drugs

Due to extensive bioprospecting efforts of the past and technology factors, there have been questions about drug discovery prospect from untapped species. We analyzed recent trends of approved drugs derived from previously untapped species, which show no sign of untapped drug-productive species being near extinction and suggest high probability of deriving new drugs from new species in existing drug-productive species families and clusters. Case histories of recently approved drugs reveal useful strategies for deriving new drugs from the scaffolds and pharmacophores of the natural product leads of these untapped species. New technologies such as cryptic gene-cluster exploration may generate novel natural products with highly anticipated potential impact on drug discovery.