Leaf size of woody dicots predicts ecosystem primary productivity

A key challenge in ecology is to understand the relationships between organismal traits and ecosystem processes. Here, with a novel dataset of leaf length and width for 10 480 woody dicots in China and 2374 in North America, we show that the variation in community mean leaf size is highly correlated with the variation in climate and ecosystem primary productivity, independent of plant life form. These relationships likely reflect how natural selection modifies leaf size across varying climates in conjunction with how climate influences canopy total leaf area. We find that the leaf size?primary productivity functions based on the Chinese dataset can predict productivity in North America and vice‐versa. In addition to advancing understanding of the relationship between a climate‐driven trait and ecosystem functioning, our findings suggest that leaf size can also be a promising tool in palaeoecology for scaling from fossil leaves to palaeo‐primary productivity of woody ecosystems.     

Meningococcal disease: A paradigm of type‐IV pilus dependent pathogenesis

Neisseria meningitidis (meningococcus) is a Gram‐negative bacterium responsible for two devastating forms of invasive diseases: purpura fulminans and meningitis. Interaction with both peripheral and cerebral microvascular endothelial cells is at the heart of meningococcal pathogenesis. During the last two decades, an essential role for meningococcal type IV pili in vascular colonisation and disease progression has been unravelled. This review summarises 20 years of research on meningococcal type IV pilus‐dependent virulence mechanisms, up to the identification of promising anti‐virulence compounds that target type IV pili.     

Bacteriostatic and Bactericidal Activities of Camel Lactoferrins Against Salmonella enterica Serovar Typhi

Probiotics and Antimicrobial Proteins - Lactoferrin is an iron-binding glycoprotein present in various secretions (e.g., milk, tears, saliva, pancreatic juice), which performs multiple functions,...     

Predicting beta-turns in proteins using support vector machines with fractional polynomials

Background

β-turns are secondary structure type that have essential role in molecular recognition, protein folding, and stability. They are found to be the most common type of non-repetitive structures since 25% of amino acids in protein structures are situated on them. Their prediction is considered to be one of the crucial problems in bioinformatics and molecular biology, which can provide valuable insights and inputs for the fold recognition and drug design.

Results

We propose an approach that combines support vector machines (SVMs) and logistic regression (LR) in a hybrid prediction method, which we call (H-SVM-LR) to predict β-turns in proteins. Fractional polynomials are used for LR modeling. We utilize position specific scoring matrices (PSSMs) and predicted secondary structure (PSS) as features. Our simulation studies show that H-SVM-LR achieves Qtotal of 82.87%, 82.84%, and 82.32% on the BT426, BT547, and BT823 datasets respectively. These values are the highest among other β-turns prediction methods that are based on PSSMs and secondary structure information. H-SVM-LR also achieves favorable performance in predicting β-turns as measured by the Matthew's correlation coefficient (MCC) on these datasets. Furthermore, H-SVM-LR shows good performance when considering shape strings as additional features.

Conclusions

In this paper, we present a comprehensive approach for β-turns prediction. Experiments show that our proposed approach achieves better performance compared to other competing prediction methods.

     

Can Inpatient Hospital Experiences Predict Central Line-Associated Bloodstream Infections?

Background

Factors that increase the risk of central line-associated bloodstream infections (CLABSIs) are not fully understood. Recently, Hospital Compare began compiling data from hospital-required reporting to the CDC''s National Healthcare Safety Network on CLABSIs in intensive care units (ICUs), at over 4,000 Medicare-certified hospitals in the United States, and made this data accessible on a central website. Also available on the same website are results from the Hospital Consumer Assessment of Healthcare Providers and Systems survey of patients'' hospital experiences. Utilizing both databases, our objective was to determine whether patients'' hospital experiences were significantly associated with increased risk for reported ICU CLABSI.

Methods and Findings

We conducted a zero-inflated Poisson regression analysis at the hospital level on CLABSI-observed cases by ICUs in acute care hospitals (n = 1987) in the United States between January 1, 2011, and December 31, 2011. During this period there were a total of 10,866 CLABSI cases and 9,543,765 central line days. In our final model, the percent of patients who reported that they “sometimes” or “never” received help as soon as they wanted was significantly associated with an increased risk for CLABSIs.

Conclusions

Using national datasets, we found that inpatients'' hospital experiences were significantly associated with an increased risk of ICU reported CLABSIs. This study suggests that hospitals with lower staff responsiveness, perhaps because of an understaffing of nurse and supportive personnel, are at an increased risk for CLABSIs. This study bolsters the evidence that patient surveys may be a useful surrogate to predicting the incidence of hospital acquired conditions, including CLABSIs. Moreover, our study found that poor staff responsiveness may be indicative of greater hospital problems and generally poorly performing hospitals; and that this finding may be a symptom of hospitals with a multitude of problems, including patient safety problems, and not a direct cause.     

Synthesis of gatifloxacin derivatives and their biological activities against Mycobacterium leprae and Mycobacterium tuberculosis

Novel 3′-piperazinyl derivatives of the 8-hydrogeno and 8-methoxy-6-fluoro-1-cyclopropyl-4-quinolone-3-carboxylic acid scaffolds were designed, synthesized and characterized by ¹H, ¹³C and ¹⁹F NMR, and HRMS. The activity of these derivatives against pathogenic mycobacteria (M. leprae and M. tuberculosis), wild-type (WT) strains or strains harboring mutations implicated in quinolone resistance, were determined by measuring drug concentrations inhibiting cell growth (MIC) and/or DNA supercoiling by DNA gyrase (IC₅₀), or inducing 25% DNA cleavage by DNA gyrase (CC₂₅). Compound 4 (with a methoxy in R₈ and a secondary carbamate in R₃′) and compound 5 (with a hydrogen in R₈ and an ethyl ester in R₃′) displayed biological activities close to those of ofloxacin but inferior to those of gatifloxacin and moxifloxacin against M. tuberculosis and M. leprae WT DNA gyrases, whereas all of the compounds were less active in inhibiting M. tuberculosis growth and M. leprae mutant DNA gyrases. Since R₃′ substitutions have been poorly investigated previously, our results may help to design new quinolone derivatives in the future.     

Influence of age on the bioaccumulation of heavy metals in Apodemus sylvaticus at Merja Zerga lagoon,Morocco

The influence of age and sex on the bioaccumulation of heavy metals in Apodemus sylvaticus was studied in Merja Zerga lagoon in northern Morocco. Five trace metal elements (Zn, Pb, Cr, Cu and Fe) were quantitatively analyzed by Varian AA 240 atomic absorption spectroscopy with graphite furnace in three organs (Liver, Kidney and Heart) from animals of different age and sex. The maximum metal level of the analyzed samples was recorded in adults and was limited to 46.62 μg/g for Pb and 35.1 μg/g for Cu, while it reached 22.69 μg/g, 7.59 μg/g and 6.78 μg/g for Cr, Zn and Fe, respectively. Highly significant differences were found for bioaccumulation of heavy metals according to animal ages and no significant differences were observed between the two sexes among the studied animals. Our results revealed also the existence of a strong correlation (r > 0.65) between the majority of biometric parameters and the trace element concentrations. In general, we found that age is a critical factor in estimating the level of heavy metal pollution. Other characteristics such as habitat, feeding habits and anti-predator behavior of the species need to be studied.