Identification of 2-Aminothiazole-4-Carboxylate Derivatives Active against Mycobacterium tuberculosis H37Rv and the β-Ketoacyl-ACP Synthase mtFabH

Background Tuberculosis (TB) is a disease which kills two million people every year and infects approximately over one-third of the world's population. The difficulty in managing tuberculosis is the prolonged treatment duration, the emergence of drug resistance and co-infection with HIV/AIDS. Tuberculosis control requires new drugs that act at novel drug targets to help combat resistant forms of Mycobacterium tuberculosis and reduce treatment duration. Methodology/Principal Findings Our approach was to modify the naturally occurring and synthetically challenging antibiotic thiolactomycin (TLM) to the more tractable 2-aminothiazole-4-carboxylate scaffold to generate compounds that mimic TLM's novel mode of action. We report here the identification of a series of compounds possessing excellent activity against M. tuberculosis H37Rv and, dissociatively, against the β-ketoacyl synthase enzyme mtFabH which is targeted by TLM. Specifically, methyl 2-amino-5-benzylthiazole-4-carboxylate was found to inhibit M. tuberculosis H37Rv with an MIC of 0.06 µg/ml (240 nM), but showed no activity against mtFabH, whereas methyl 2-(2-bromoacetamido)-5-(3-chlorophenyl)t​hiazole-4-carboxylateinhibited mtFabH with an IC50 of 0.95±0.05 µg/ml (2.43±0.13 µM) but was not active against the whole cell organism. Conclusions/Significance These findings clearly identify the 2-aminothiazole-4-carboxylate scaffold as a promising new template towards the discovery of a new class of anti-tubercular agents

Identifying component modules

A computer-based system for modelling component dependencies and identifying component modules is presented. A variation of the Dependency Structure Matrix (DSM) representation was used to model component dependencies. The system utilises a two-stage approach towards facilitating the identification of a hierarchical modular structure. The first stage calculates a value for a clustering criterion that may be used to group component dependencies together. A Genetic Algorithm is described to optimise the order of the components within the DSM with the focus of minimising the value of the clustering criterion to identify the most significant component groupings (modules) within the product structure. The second stage utilises a 'Module Strength Indicator' (MSI) function to determine a value representative of the degree of modularity of the component groupings. The application of this function to the DSM produces a 'Module Structure Matrix' (MSM) depicting the relative modularity of available component groupings within it. The approach enabled the identification of hierarchical modularity in the product structure without the requirement for any additional domain specific knowledge within the system. The system supports design by providing mechanisms to explicitly represent and utilise component and dependency knowledge to facilitate the nontrivial task of determining near-optimal component modules and representing product modularity

Juvenile myoclonic epilepsy presenting as a new daily persistent-like headache

New daily persistent headache (NDPH) is a recognized subtype of chronic daily headache with a unique presentation of a daily headache from onset typically in individuals with minimal or no prior headache history. Various secondary mimics of NDPH have now been documented but at present there has been no association made between primary epilepsy syndromes and new daily persistent-like headaches. A case patient is presented who developed a daily continuous headache from onset who 3 months after headache initiation had her first generalized tonic-clonic seizure. Further investigation into her history and her specific EEG pattern suggested a diagnosis of juvenile myoclonic epilepsy (JME). Her NDPH and seizures ceased with epilepsy treatment. Clinically relevant was that the headache was the primary persistent clinical symptom of her JME before the onset of generalized tonic-clonic seizures. The current case report adds another possible secondary cause of new daily persistent-like headaches to the medical literature and suggests another association between primary epilepsy syndromes and distinct headache syndromes

Impact of progressive global warming on the global-scale yield of maize and soybean

Global surface temperature is projected to warm over the coming decades, with regional differences expected in temperature change, rainfall and the frequency of extreme events. Temperature is a major determinant of crop growth and development, affecting planting date, growing season length and yield. We investigated the effects of increments of mean global temperature warming from 0.5 °C to 4 °C on soybean and maize development and yield, both globally and for the main producing countries, and simulated adaptation through changing planting date and variety. Increasing temperature resulted in reduced growing season lengths and ultimately reduced yields for both crops. The global yield for maize decreased as temperature increased, although the severity of the decrease was dependent on geographic region. Small temperature increases of 0.5 °C had no effect on soybean yield, although yield decreased as temperature increased. These negative effects, however, were partly compensated for by the implementation of adaptation strategies including planting earlier in the season and changing variety. The degree of compensation was dependent on geographical area and crop, with maize adaptation delaying the negative effects of temperature on yield, compared to soybean adaptation which increased yield in China, India and Korea DPR as well as delaying the effects in the remaining countries. The results of this paper indicate the degree to which farmer-controlled adaptation strategies can alleviate the negative impacts of increasing temperature on two major crop species

Collision Mortality Has No Discernible Effect on Population Trends of North American Birds

Avian biodiversity is threatened by numerous anthropogenic factors and migratory species are especially at risk. Migrating birds frequently collide with manmade structures and such losses are believed to represent the majority of anthropogenic mortality for North American birds. However, estimates of total collision mortality range across several orders of magnitude and effects on population dynamics remain unknown. Herein, we develop a novel method to assess relative vulnerability to anthropogenic threats, which we demonstrate using 243,103 collision records from 188 species of eastern North American landbirds. After correcting mortality estimates for variation attributable to population size and geographic overlap with potential collision structures, we found that per capita vulnerability to collision with buildings and towers varied over more than four orders of magnitude among species. Species that migrate long distances or at night were much more likely to be killed by collisions than year-round residents or diurnal migrants. However, there was no correlation between relative collision mortality and long-term population trends for these same species. Thus, although millions of North American birds are killed annually by collisions with manmade structures, this source of mortality has no discernible effect on populations

The p53HMM algorithm: using profile hidden markov models to detect p53-responsive genes

<p>Abstract</p> <p>Background</p> <p>A computational method (called p53HMM) is presented that utilizes Profile Hidden Markov Models (PHMMs) to estimate the relative binding affinities of putative p53 response elements (REs), both p53 single-sites and cluster-sites. These models incorporate a novel "Corresponded Baum-Welch" training algorithm that provides increased predictive power by exploiting the redundancy of information found in the repeated, palindromic p53-binding motif. The predictive accuracy of these new models are compared against other predictive models, including position specific score matrices (PSSMs, or weight matrices). We also present a new dynamic acceptance threshold, dependent upon a putative binding site's distance from the Transcription Start Site (TSS) and its estimated binding affinity. This new criteria for classifying putative p53-binding sites increases predictive accuracy by reducing the false positive rate.</p> <p>Results</p> <p>Training a Profile Hidden Markov Model with corresponding positions matching a combined-palindromic p53-binding motif creates the best p53-RE predictive model. The p53HMM algorithm is available on-line: <url>http://tools.csb.ias.edu</url></p> <p>Conclusion</p> <p>Using Profile Hidden Markov Models with training methods that exploit the redundant information of the homotetramer p53 binding site provides better predictive models than weight matrices (PSSMs). These methods may also boost performance when applied to other transcription factor binding sites.</p

Large differences in regional precipitation change between a first and second 2 K of global warming

For adaptation and mitigation planning, stakeholders need reliable information about regional precipitation changes under different emissions scenarios and for different time periods. A significant amount of current planning effort assumes that each K of global warming produces roughly the same regional climate change. Here using 25 climate models, we compare precipitation responses with three 2 K intervals of global ensemble mean warming: a fast and a slower route to a first 2 K above pre-industrial levels, and the end-of-century difference between high-emission and mitigation scenarios. We show that, although the two routes to a first 2 K give very similar precipitation changes, a second 2 K produces quite a different response. In particular, the balance of physical mechanisms responsible for climate model uncertainty is different for a first and a second 2 K of warming. The results are consistent with a significant influence from nonlinear physical mechanisms, but aerosol and land-use effects may be important regionally

Memory-experience gap in early adolescents' happiness reports

Studies among adult populations show that estimates of how happy one has felt in the past tend to be more positive than average happiness as assessed using time sampling techniques. This ‘memory-experience gap’ is attributed to cognitive biases, among which fading affect bias. In this paper we report a study among 352 pupils of a secondary school in the Netherlands. These youngsters reported subsequently: 1) how happy they had felt yesterday, 2) how happy they had felt during the last month, 3) what they had done the previous day and 4) how the

Neural Mechanisms of Interference Control in Working Memory: Effects of Interference Expectancy and Fluid Intelligence

A critical aspect of executive control is the ability to limit the adverse effects of interference. Previous studies have shown activation of left ventrolateral prefrontal cortex after the onset of interference, suggesting that interference may be resolved in a reactive manner. However, we suggest that interference control may also operate in a proactive manner to prevent effects of interference. The current study investigated the temporal dynamics of interference control by varying two factors - interference expectancy and fluid intelligence (gF) - that could influence whether interference control operates proactively versus reactively.A modified version of the recent negatives task was utilized. Interference expectancy was manipulated across task blocks by changing the proportion of recent negative (interference) trials versus recent positive (facilitation) trials. Furthermore, we explored whether gF affected the tendency to utilize specific interference control mechanisms. When interference expectancy was low, activity in lateral prefrontal cortex replicated prior results showing a reactive control pattern (i.e., interference-sensitivity during probe period). In contrast, when interference expectancy was high, bilateral prefrontal cortex activation was more indicative of proactive control mechanisms (interference-related effects prior to the probe period). Additional results suggested that the proactive control pattern was more evident in high gF individuals, whereas the reactive control pattern was more evident in low gF individuals.The results suggest the presence of two neural mechanisms of interference control, with the differential expression of these mechanisms modulated by both experimental (e.g., expectancy effects) and individual difference (e.g., gF) factors

HIF-1 and SKN-1 Coordinate the Transcriptional Response to Hydrogen Sulfide in Caenorhabditis elegans

Hydrogen sulfide (H2S) has dramatic physiological effects on animals that are associated with improved survival. C. elegans grown in H2S are long-lived and thermotolerant. To identify mechanisms by which adaptation to H2S effects physiological functions, we have measured transcriptional responses to H2S exposure. Using microarray analysis we observe rapid changes in the abundance of specific mRNAs. The number and magnitude of transcriptional changes increased with the duration of H2S exposure. Functional annotation suggests that genes associated with protein homeostasis are upregulated upon prolonged exposure to H2S. Previous work has shown that the hypoxia-inducible transcription factor, HIF-1, is required for survival in H2S. In fact, we show that hif-1 is required for most, if not all, early transcriptional changes in H2S. Moreover, our data demonstrate that SKN-1, the C. elegans homologue of NRF2, also contributes to H2S-dependent changes in transcription. We show that these results are functionally important, as skn-1 is essential to survive exposure to H2S. Our results suggest a model in which HIF-1 and SKN-1 coordinate a broad transcriptional response to H2S that culminates in a global reorganization of protein homeostasis networks