In Vitro Activity of a Novel Glycopolymer against Biofilms of Burkholderia cepacia Complex Cystic Fibrosis Clinical Isolates.

Burkholderia cepacia complex (Bcc) lung infections in cystic fibrosis (CF) patients are often associated with a steady decline in lung function and death. The formation of biofilms and inherent multidrug resistance are virulence factors associated with Bcc infection and contribute to increased risk of mortality in CF patients. New therapeutic strategies targeting bacterial biofilms are anticipated to enhance antibiotic penetration and facilitate resolution of infection. Poly (acetyl, arginyl) glucosamine (PAAG) is a cationic glycopolymer therapeutic being developed to directly target biofilm integrity. In this study, 13 isolates from 7 species were examined, including Burkholderia multivorans, Burkholderia cenocepacia, Burkholderia gladioli, Burkholderia dolosa, Burkholderia vietnamiensis, and B. cepacia These isolates were selected for their resistance to standard clinical antibiotics and their ability to form biofilms in vitro Biofilm biomass was quantitated using static tissue culture plate (TCP) biofilm methods and a minimum biofilm eradication concentration (MBEC) assay. Confocal laser scanning microscopy (CLSM) visualized biofilm removal by PAAG during treatment. Both TCP and MBEC methods demonstrated a significant dose-dependent relationship with regard to biofilm removal by 50 to 200 µg/ml PAAG following a 1-h treatment (P < 0.01). A significant reduction in biofilm thickness was observed following a 10-min treatment of Bcc biofilms with PAAG compared to that with vehicle control (P < 0.001) in TCP, MBEC, and CLSM analyses. PAAG also rapidly permeabilizes bacteria within the first 10 min of treatment. Glycopolymers, such as PAAG, are a new class of large-molecule therapeutics that support the treatment of recalcitrant Bcc biofilm.

Predicting culturable enterococci exceedances at Escambron Beach, San Juan, Puerto Rico using satellite remote sensing and artificial neural networks.

Predicting recreational water quality is key to protecting public health from exposure to wastewater-associated pathogens. It is not feasible to monitor recreational waters for all pathogens; therefore, monitoring programs use fecal indicator bacteria (FIB), such as enterococci, to identify wastewater pollution. Artificial neural networks (ANNs) were used to predict when culturable enterococci concentrations exceeded the U.S. Environmental Protection Agency (U.S. EPA) Recreational Water Quality Criteria (RWQC) at Escambron Beach, San Juan, Puerto Rico. Ten years of culturable enterococci data were analyzed together with satellite-derived sea surface temperature (SST), direct normal irradiance (DNI), turbidity, and dew point, along with local observations of precipitation and mean sea level (MSL). The factors identified as the most relevant for enterococci exceedance predictions based on the U.S. EPA RWQC were DNI, turbidity, cumulative 48 h precipitation, MSL, and SST; they predicted culturable enterococci exceedances with an accuracy of 75% and power greater than 60% based on the Receiving Operating Characteristic curve and F-Measure metrics. Results show the applicability of satellite-derived data and ANNs to predict recreational water quality at Escambron Beach. Future work should incorporate local sanitary survey data to predict risky recreational water conditions and protect human health.

Application of Artificial Neural Networks for Dengue Fever Outbreak Predictions in the Northwest Coast of Yucatan, Mexico and San Juan, Puerto Rico.

Modelling dengue fever in endemic areas is important to mitigate and improve vector-borne disease control to reduce outbreaks. This study applied artificial neural networks (ANNs) to predict dengue fever outbreak occurrences in San Juan, Puerto Rico (USA), and in several coastal municipalities of the state of Yucatan, Mexico, based on specific thresholds. The models were trained with 19 years of dengue fever data for Puerto Rico and six years for Mexico. Environmental and demographic data included in the predictive models were sea surface temperature (SST), precipitation, air temperature (i.e., minimum, maximum, and average), humidity, previous dengue cases, and population size. Two models were applied for each study area. One predicted dengue incidence rates based on population at risk (i.e., numbers of people younger than 24 years), and the other on the size of the vulnerable population (i.e., number of people younger than five years and older than 65 years). The predictive power was above 70% for all four model runs. The ANNs were able to successfully model dengue fever outbreak occurrences in both study areas. The variables with the most influence on predicting dengue fever outbreak occurrences for San Juan, Puerto Rico, included population size, previous dengue cases, maximum air temperature, and date. In Yucatan, Mexico, the most important variables were population size, previous dengue cases, minimum air temperature, and date. These models have predictive skills and should help dengue fever mitigation and management to aid specific population segments in the Caribbean region and around the Gulf of Mexico.

Rearrangements and stereomutations of metallacycles derived from allenes and imidozirconium complexes.

The mechanisms of the rearrangements and stereoinversion of azametallacyclobutenes generated via [2+2] cycloaddition of allenes and imidozirconium complexes have been studied. Metallacycles derived from allenes bearing beta-hydrogen atoms racemize at room temperature by reversible beta-hydride elimination, a process which is also responsible for their eventual conversion to monoazadiene complexes. Metallacycles derived from diarylallenes racemize by reversible thermal bond homolysis at 95 degrees C; racemization of these metallacycles is also catalyzed by mild oxidants.

Enantioselective Cu-catalyzed conjugate addition of diethylzinc to acyclic aliphatic enones.

[reaction: see text] A new P-chiral phosphine bis(sulfonamide) ligand has been developed that allows the Cu-catalyzed enantioselective conjugate addition of Et(2)Zn to acyclic aliphatic enones. The reactions proceed with excellent levels of enantioselectivity (90-95% ee) with a range of enone substrates, involve the use of only 1.2 equiv of Et(2)Zn, and give best results at ambient temperature.

Mechanisms of allene stereoinversion by imidozirconium complexes.

The zirconium-mediated stereoinversion of allenes has been investigated by studying the stereochemical behavior of metallacycles derived from [2 + 2] cycloaddition of enantioenriched allenes with chiral and achiral imidozirconocene complexes. Relative rates of metallacycle racemization were measured by circular dichroism, and intermediates in the selective stereoinversion of diphenylallene with a chiral imidozirconium complex were observed by NMR spectroscopy. Metallacycles derived from dialkylallenes are proposed to racemize via reversible beta-hydride elimination. Stereoinversion of diarylallene-derived metallacycles proceeds much more slowly and is thought to proceed through an eta4-azatrimethylenemethane transition state.

Selective transformations of organic compounds by imidozirconocene complexes.

Imidozirconocene complexes (Cp(2)Zr=NR(THF)) possess a rich reaction chemistry, in contrast to many imido complexes of later transition metals. The synthesis and structural characteristics of these compounds are briefly described, along with a qualitative molecular orbital description of the metallocene-imido interaction. Imidozirconocene complexes react at the Zr=N linkage with a variety of X-H bonds, and undergo overall [2 + 2] cycloaddition reactions with a wide range of unsaturated organic and organometallic compounds. Results of studies detailing the scope and mechanism of these reactions are presented herein, along with applications to catalytic hydroamination, imine metathesis, and asymmetric transformations.