Missense mutation of Brain Derived Neurotrophic Factor (BDNF) alters neurocognitive performance in patients with mild traumatic brain injury: a longitudinal study

The predictability of neurocognitive outcomes in patients with traumatic brain injury is not straightforward. The extent and nature of recovery in patients with mild traumatic brain injury (mTBI) are usually heterogeneous and not substantially explained by the commonly known demographic and injury-related prognostic factors despite having sustained similar injuries or injury severity. Hence, this study evaluated the effects and association of the Brain Derived Neurotrophic Factor (BDNF) missense mutations in relation to neurocognitive performance among patients with mTBI. 48 patients with mTBI were prospectively recruited and MRI scans of the brain were performed within an average 10.1 (SD 4.2) hours post trauma with assessment of their neuropsychological performance post full Glasgow Coma Scale (GCS) recovery. Neurocognitive assessments were repeated again at 6 months follow-up. The paired t-test, Cohen’s d effect size and repeated measure ANOVA were performed to delineate statistically significant differences between the groups [wildtype G allele (Val homozygotes) vs. minor A allele (Met carriers)] and their neuropsychological performance across the time point (T1 = baseline/ admission vs. T2 = 6th month follow-up). Minor A allele carriers in this study generally performed more poorly on neuropsychological testing in comparison wildtype G allele group at both time points. Significant mean differences were observed among the wildtype group in the domains of memory (M = -11.44, SD = 10.0, p = .01, d = 1.22), executive function (M = -11.56, SD = 11.7, p = .02, d = 1.05) and overall performance (M = -6.89 SD = 5.3, p = .00, d = 1.39), while the minor A allele carriers showed significant mean differences in the domains of attention (M = -11.0, SD = 13.1, p = .00, d = .86) and overall cognitive performance (M = -5.25, SD = 8.1, p = .01, d = .66).The minor A allele carriers in comparison to the wildtype G allele group, showed considerably lower scores at admission and remained impaired in most domains across the timepoints, although delayed signs of recovery were noted to be significant in the domains attention and overall cognition. In conclusion, the current study has demonstrated the role of the BDNF rs6265 Val66Met polymorphism in influencing specific neurocognitive outcomes in patients with mTBI. Findings were more detrimentally profound among Met allele carriers

Future and potential spending on health 2015-40: development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries

Background The amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending. Methods We extracted GDP, government spending in 184 countries from 1980–2015, and health spend data from 1995–2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted. Findings We estimated that global spending on health will increase from US$9·21 trillion in 2014 to$24·24 trillion (uncertainty interval [UI] 20·47–29·72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5·3% (UI 4·1–6·8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4·2% (3·8–4·9). High-income countries are expected to grow at 2·1% (UI 1·8–2·4) and low-income countries are expected to grow at 1·8% (1·0–2·8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at $154 (UI 133–181) per capita in 2030 and$195 (157–258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157–258) per capita was available for health in 2040 in low-income countries. Interpretation Health spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential

Cholera- and Anthrax-Like Toxins Are among Several New ADP-Ribosyltransferases

Chelt, a cholera-like toxin from Vibrio cholerae, and Certhrax, an anthrax-like toxin from Bacillus cereus, are among six new bacterial protein toxins we identified and characterized using in silico and cell-based techniques. We also uncovered medically relevant toxins from Mycobacterium avium and Enterococcus faecalis. We found agriculturally relevant toxins in Photorhabdus luminescens and Vibrio splendidus. These toxins belong to the ADP-ribosyltransferase family that has conserved structure despite low sequence identity. Therefore, our search for new toxins combined fold recognition with rules for filtering sequences – including a primary sequence pattern – to reduce reliance on sequence identity and identify toxins using structure. We used computers to build models and analyzed each new toxin to understand features including: structure, secretion, cell entry, activation, NAD+ substrate binding, intracellular target binding and the reaction mechanism. We confirmed activity using a yeast growth test. In this era where an expanding protein structure library complements abundant protein sequence data – and we need high-throughput validation – our approach provides insight into the newest toxin ADP-ribosyltransferases

On the Evolutionary Origin of Eukaryotic DNA Methyltransferases and Dnmt2

The Dnmt2 enzymes show strong amino acid sequence similarity with eukaryotic and prokaryotic DNA-(cytosine C5)-methyltransferases. Yet, Dnmt2 enzymes from several species were shown to methylate tRNA-Asp and had been proposed that eukaryotic DNA methyltransferases evolved from a Dnmt2-like tRNA methyltransferase ancestor [Goll et al., 2006, Science, 311, 395-8]. It was the aim of this study to investigate if this hypothesis could be supported by evidence from sequence alignments. We present phylogenetic analyses based on sequence alignments of the methyltransferase catalytic domains of more than 2300 eukaryotic and prokaryotic DNA-(cytosine C5)-methyltransferases and analyzed the distribution of DNA methyltransferases in eukaryotic species. The Dnmt2 homologues were reliably identified by an additional conserved CFT motif next to motif IX. All DNA methyltransferases and Dnmt2 enzymes were clearly separated from other RNA-(cytosine-C5)-methyltransferases. Our sequence alignments and phylogenetic analyses indicate that the last universal eukaryotic ancestor contained at least one member of the Dnmt1, Dnmt2 and Dnmt3 families of enzymes and additional RNA methyltransferases. The similarity of Dnmt2 enzymes with DNA methyltransferases and absence of similarity with RNA methyltransferases combined with their strong RNA methylation activity suggest that the ancestor of Dnmt2 was a DNA methyltransferase and an early Dnmt2 enzyme changed its substrate preference to tRNA. There is no phylogenetic evidence that Dnmt2 was the precursor of eukaryotic Dnmts. Most likely, the eukaryotic Dnmt1 and Dnmt3 families of DNA methyltransferases had an independent origin in the prokaryotic DNA methyltransferase sequence space

HIV protease inhibitor resistance

HIV protease is pivotal in the viral replication cycle and directs the formation of mature infectious virus particles. The development of highly specific HIV protease inhibitors (PIs), based on thorough understanding of the structure of HIV protease and its substrate, serves as a prime example of structure-based drug design. The introduction of first-generation PIs marked the start of combination antiretroviral therapy. However, low bioavailability, high pill burden, and toxicity ultimately reduced adherence and limited long-term viral inhibition. Therapy failure was often associated with multiple protease inhibitor resistance mutations, both in the viral protease and its substrate (HIV gag protein), displaying a broad spectrum of resistance mechanisms. Unfortunately, selection of protease inhibitor resistance mutations often resulted in cross-resistance to other PIs. Therefore, second-generation approaches were imperative. Coadministration of a cytochrome P-450 3A4 inhibitor greatly improved the plasma concentration of PIs in the patient. A second advance was the development of PIs that were efficacious against first-generation PI-resistant HIV. Both approaches increased the number of protease mutations required by the virus to develop clinically relevant resistance, thereby raising the genetic barrier towards PI resistance. These improvements greatly contributed to the success of PI-based therapy