Riboflavin induces Metarhizium spp. to produce conidia with elevated tolerance to UV-B, and upregulates photolyases, laccases and polyketide synthases genes.

AIMS: The effect of nutritional supplementation of two Metarhizium species with riboflavin (Rb) during production of conidia was evaluated on (i) conidial tolerance (based on germination) to UV-B radiation and on (ii) conidial expression following UV-B irradiation, of enzymes known to be active in photoreactivation, viz., photolyase (Phr), laccase (Lac) and polyketide synthase (Pks). METHODS AND RESULTS: Metarhizium acridum (ARSEF 324) and Metarhizium robertsii (ARSEF 2575) were grown either on (i) potato dextrose agar medium (PDA), (ii) PDA supplemented with 1% yeast extract (PDAY), (iii) PDA supplemented with Rb (PDA+Rb), or (iv) PDAY supplemented with Rb (PDAY+Rb). Resulting conidia were exposed to 866·7 mW m-2 of UV-B Quaite-weighted irradiance to total doses of 3·9 or 6·24 kJ m-2 . Some conidia also were exposed to 16 klux of white light (WL) after being irradiated, or not, with UV-B to investigate the role of possible photoreactivation. Relative germination of conidia produced on PDA+Rb (regardless Rb concentration) or on PDAY and exposed to UV-B was higher compared to conidia cultivated on PDA without Rb supplement, or to conidia suspended in Rb solution immediately prior to UV-B exposure. The expression of MaLac3 and MaPks2 for M. acridum, as well as MrPhr2, MrLac1, MrLac2 and MrLac3 for M. robertsii was higher when the isolates were cultivated on PDA+Rb and exposed to UV-B followed by exposure to WL, or exposed to WL only. CONCLUSIONS: Rb in culture medium increases the UV-B tolerance of M. robertsii and M. acridum conidia, and which may be related to increased expression of Phr, Lac and Pks genes in these conidia. SIGNIFICANCE AND IMPACT OF THE STUDY: The enhanced UV-B tolerance of Metarhizium spp. conidia produced on Rb-enriched media may improve the effectiveness of these fungi in biological control programs.

The implantation effect: delay in seizure occurrence with implantation of intracranial electrodes.

OBJECTIVE: A transient decrease in seizure frequency has been identified during therapeutic brain stimulation trials with stimulator in patients in the inactive sham group. This study was performed to examine whether the implantation of intracranial electrodes decreases seizure occurrence and explores factors that may be associated. METHODS: A retrospective review of 193 patients was performed, all evaluated with both scalp video EEG monitoring and intracranial EEG (iEEG) monitoring. Data about the number of seizures per day during the monitoring period, the number of days until the first seizure, anti-epileptic drugs (AEDs), pain medications, types of implanted electrodes, and anesthetic agents were reviewed. We conducted a repeated measure analysis for counted data using generalized estimating equations with a log-link function and adjustment for number of days and anti-epileptic medication load on the previous day to compare seizure frequencies between scalp and iEEG monitoring. RESULTS: The time to the first seizure was significantly prolonged during iEEG monitoring as compared to scalp monitoring after correction for AED withdrawal (hazard ratio: 0.81, CI 0.69-0.96). During scalp video EEG monitoring, patients experienced an average of 1.09 seizures/day vs 1.27 seizures/day during iEEG monitoring (P=.066). There was no significant difference in seizure frequency in patients that received craniotomy vs burr holes only for intracranial implantation. An increasing number of electrodes implanted increased the delay to seizures (P=.01). Of all anesthetic agents used, desflurane seemed to have an anticonvulsive effect compared to other anesthetics (P=.006). Pain medication did not influence delay to seizures. SIGNIFICANCE: Seizures are delayed during iEEG as opposed to scalp monitoring illustrating the "implantation effect" previously observed. Surgical planning should account for longer monitoring periods, particularly when using larger intracranial arrays.

Mechanism-Based QSAR Modeling of Skin Sensitization.

Many chemicals can induce skin sensitization, and there is a pressing need for non-animal methods to give a quantitative indication of potency. Using two large published data sets of skin sensitizers, we have allocated each sensitizing chemical to one of 10 mechanistic categories and then developed good QSAR models for the seven categories that have a sufficient number of chemicals to allow modeling. Both internal and external validation checks showed that each model had good predictivity.

Electrophilic reactivity and skin sensitization potency of SNAr electrophiles.

We published in 2011 a quantitative mechanistic model (QMM) for skin sensitization potency of SNAr electrophiles in the mouse local lymph node assay (LLNA). In this model, potency was correlated with a combination of σ* for the leaving group and the total σ(-) values of the other substituents in the aromatic ring. Shortly afterward Natsch et al. published a kinetic study in which rate constants were determined for reactions of SNAr electrophiles with the cysteine-based peptide Ac-RFAACAA (Cys-peptide) that is used in the direct peptide reactivity assay (DPRA), and correlations were sought between these rate constants and sensitization potency in the LLNA. These two publications together have enabled the present study, aiming to develop a linear free energy relationship (LFER) correlating Cys-peptide reactivity with a reactivity parameter (RP) based on a combination of σ* and σ(-) substituent constants and, by analyzing differences between the QMM based on RP and the QMM based on Cys-peptide rate constants, to gain further insights into the underlying chemistry of skin sensitization. For the 2,4-dinitro-X-subsituted benzenes (DNXB), the rate constants of Natsch et al. are well correlated with the reactivity parameter used in our earlier work, with two outliers. These are the compounds with X = F and X = SCN, which are both substantially more reactive toward Cys-peptide than predicted from comparison of their RP values with those of the other DNXB compounds. These two compounds are both negative outliers from a correlation of sensitization potency with experimental rate constants, but fit well to the correlation of sensitization potency with RP values. With these two compounds excluded, sensitization potency is well correlated with the experimental rate constants for the DNXB compounds (X = SO3(-), I, Br, Cl) together with 2,4-dichloro-1-nitrobenzene and 1,3,4,5-tetrachloro-2,6-dicyanobenzene. The regression equation is pEC3 = 0.88 log k + 4.03, R(2) = 0.966. The implication of DNFB being an outlier is that the model Cys-peptide nucleophile is substantially more sterically hindered than the cutaneous nucleophile(s) involved in the sensitization process. The pattern seen with 2,4-dinitrothiocyanatobenzene suggests that this compound reacts as an SNAr electrophile in the sensitization process, but by a different pathway, acting as a CN transfer agent, with the model Cys-peptide. For two further compounds, 2,4,6-trinitrochlorobenzene and 2,4,6-trinitrobenzenesulfonate, the Cys-peptide rate constants are well predicted by the reactivity parameter based on displacement of the Cl or SO3(-) substituent, but their sensitization potency is underestimated by both the Cys-peptide rate constant and this reactivity parameter. However, potency of these two compounds is well predicted by a reactivity parameter calculated on the basis of displacement of the 2-nitro group. This is interpreted as a case of sensitization being driven by the thermodynamically favored rather than the kinetically favored reaction product.

Infrared lidar observations of stratospheric aerosols.

We observed the stratospheric aerosol layer at 34° north latitude with a photon-counting 1574 nm lidar on three occasions in 2011. During all of the observations, we also operated a nearby 523.5 nm micropulse lidar and acquired National Weather Service upper air data. We analyzed the lidar data to find scattering ratio profiles and the integrated aerosol backscatter at both wavelengths and then calculated the color ratio and wavelength exponent for lidar backscattering from the stratospheric aerosols. The visible-light integrated backscatter values of the layer were in the range 2.8-3.5×10⁻4 sr⁻¹ and the infrared integrated backscatter values ranged from 2.4 to 3.7×10⁻5 sr⁻¹. The wavelength exponent was determined to be 1.9±0.2.

Predicting skin sensitization potency for Michael acceptors in the LLNA using quantum mechanics calculations.

This study outlines the development of a series of quantitative mechanistic models enabling skin sensitization potency in the LLNA to be predicted for direct acting Michael acceptors. These models utilized several computational descriptors based on knowledge of the Michael addition reaction mechanism. The key descriptor was calculated using density functional theory and modeled the stability of the reaction intermediate. A second descriptor relating to the available surface area at the site of the reaction was also found to be important. Several poorly predicted compounds were identified, and in all cases, these could be rationalized mechanistically. The analysis of these compounds allowed a well-defined mechanistically driven applicability domain to be developed. The study showed that in silico quantitative mechanistic models, with a well-defined applicability domain, can be used to predict skin sensitization potency in the LLNA. The approach presented has the potential to be of use as part of a weight of evidence approach for predicting skin sensitization without the use of animals in risk assessment.

Is diacetyl a respiratory sensitizer? A reconsideration using QSAR, QMM, and competition experiments.

Concerns have been raised that diacetyl (DA) might be a respiratory sensitizer based on its LUMO energy similar to that of the respiratory allergen toluene-2,4-diisocyanate (TDI) and results of a local lymph node assay (LLNA) that reported an EC3 of 1.9%. To better understand the concerns, we performed a systematic literature review and experimental competition reactions between DA and TDI. The experimental evidence demonstrates that DA is at least 400-fold less reactive than TDI. The literature review finds evidence that the EC3 for DA is actually >11%. We conclude that DA is unlikely to have significant respiratory sensitization potential.

A spectrally constrained dual-band normalization technique for protoporphyrin IX quantification in fluorescence-guided surgery.

We report a dual-band normalization technique for in vivo quantification of the metabolic biomarker, protoporphyrin IX (PpIX), during brain tumor resection procedures. The accuracy of the approach was optimized in tissue simulating phantoms with varying absorption and scattering properties, validated with fluorimetric assessments on ex vivo brain tissue, and tested on human data acquired in vivo during fluorescence-guided surgery of brain tumors. The results demonstrate that the dual-band normalization technique allows PpIX concentrations to be accurately quantified by correction with reflectance data recorded and integrated within only two narrow wavelength intervals. The simplicity of the method lends itself to the enticing prospect that the method could be applicable to wide-field applications in quantitative fluorescence imaging and dosimetry in photodynamic therapy.

Development of mechanism-based structural alerts for respiratory sensitization hazard identification.

This study outlines how mechanistic organic chemistry related to covalent bond formation can be used to rationalize the ability of low molecular weight chemicals to cause respiratory sensitization. The results of an analysis of 104 chemicals which have been reported to cause respiratory sensitization in humans showed that most of the sensitizing chemicals could be distinguished from 82 control chemicals for which no clinical reports of respiratory sensitization exist. This study resulted in the development of a set of mechanism-based structural alerts for chemicals with the potential to cause respiratory sensitization. Their potential for use in a predictive algorithm for this purpose alongside an externally validated quantitative structure-activity relationship model is discussed.

Pollen counts and suicide rates. Association not replicated.

OBJECTIVE: To replicate a previously reported association between pollen counts and county suicide rates in the continental United States, across space and time. METHOD: The authors evaluated the relationship between airborne pollen counts and suicide rates in 42 counties of the continental United States, containing a pollen-counting station participating in the Aeroallergen Monitoring Network in the United States (N = 120,076 suicides), considering years' quarter, age group, sex, race, rural/urban location, number of local psychiatrists, and median household income, from 1999 to 2002. The county-level effects were broken into between-county and within-county. RESULTS: No within-county effects were found. Between-county effects for grass and ragweed pollen on suicide rates lost statistical significance after adjustment for median income, number of psychiatrists, and urban vs. rural location. CONCLUSION: Future research is necessary to reappraise the previously reported relationship between pollen levels and suicide rates that may have been driven by socioeconomic confounders.

Chemistry-based risk assessment for skin sensitization: quantitative mechanistic modeling for the S(N)Ar domain.

There is a strong impetus to develop nonanimal based methods to predict skin sensitization potency. An approach based on physical organic chemistry, whereby chemicals are classified into reaction mechanistic domains and quantitative models or read-across methods are derived for each domain, has been the basis of several recent publications. This article is concerned with the S(N)Ar reaction mechanistic domain. Electrophiles able to react by the S(N)Ar mechanism have long been recognized as skin sensitizers and have been used extensively in research studies on the biology of skin sensitization. Although qualitative discriminant analysis approaches have been developed for estimating the sensitization potential for S(N)Ar electrophiles on a yes/no qualitative basis, no quantitative mechanistic model (QMM) has so far been developed for this domain. Here, we derive a QMM that correlates skin sensitization potency, quantified by murine local lymph node assay (LLNA) EC3 data on a range of S(N)Ar electrophiles. It is based on the Hammett σ(-) values for the activating groups and the Taft σ* value for the leaving group. The model takes the form pEC3=2.48 Σσ(-) + 0.60 σ* - 4.51. This QMM, generated from mouse LLNA data, provides a reactivity parameter 2.48 Σσ(-) + 0.60 σ*, which was applied to a set of 20 compounds for which guinea pig test results were available in the literature and was found to successfully discriminate the sensitizers from the nonsensitizers. The reactivity parameter correctly predicted a known human sensitizer 2,4-dichloropyrimidine. New LLNA data on two further S(N)Ar electrophiles are consistent with the QMM.

Mechanistic category formation for the prediction of respiratory sensitization.

This study investigates the ability of a set of previously published rules for protein binding, developed from skin sensitization data, to group chemicals into mechanistic domains and to develop knowledge on the chemical interactions relating to respiratory sensitization. The results of the analysis showed that 32 of 39 respiratory sensitizing chemicals could be assigned to a mechanistic domain based on the published rules. Analysis of the remaining six chemicals showed them to have electrophilic mechanisms that had not been explicitly covered by the skin sensitization protein binding rules. The study also highlighted the ability to develop subdomains within the mechanistic domains on the basis of simple chemistry principles. These subdomains were developed to allow a calculated electrophilic index to rationalize the differing respiratory sensitizing potentials of the chemicals assigned to them. The study clearly highlights how assigning the most likely mechanism of action for a chemical is useful in building chemical categories (domains) and subcategories (subdomains).

Characterization of Metarhizium species and varieties based on molecular analysis, heat tolerance and cold activity.

AIMS: The genetic relationships and conidial tolerances to high and low temperatures were determined for isolates of several Metarhizium species and varieties. METHODS AND RESULTS: Molecular-based techniques [AFLP and rDNA (ITS1, ITS2 and 5.8S) gene sequencing] were used to characterize morphologically identified Metarhizium spp. isolates from a wide range of sources. Conidial suspensions of isolates were exposed to wet heat (45 + or - 0.2 degrees C) and plated on potato dextrose agar plus yeast extract (PDAY) medium. After 8-h exposure, the isolates divided clearly into two groups: (i) all isolates of Metarhizium anisopliae var. anisopliae (Ma-an) and Metarhizium from the flavoviride complex (Mf) had virtually zero conidial relative germination (RG), (ii) Metarhizium anisopliae var. acridum (Ma-ac) isolates demonstrated high heat tolerance (c. 70-100% RG). Conidial suspensions also were plated on PDAY and incubated at 5 degrees C for 15 days, during which time RGs for Ma-an and Ma-ac isolates were virtually zero, whereas the two Mf were highly cold active (100% RG). CONCLUSIONS: Heat and cold exposures can be used as rapid tools to tentatively identify some important Metarhizium species and varieties. SIGNIFICANCE AND IMPACT OF THE STUDY: Identification of Metarhizium spp. currently relies primarily on DNA-based methods; we suggest a simple temperature-based screen to quickly obtain tentative identification of isolates as to species or species complexes.

Practical methods for the measurement of logP for surfactants.

Hydrophobicity is a commonly used parameter in quantitative structure activity relationships. The ability to determine the octanol-water partition coefficient (logP) empirically for non-ionizing, non-surfactant type chemicals using traditional stir-flask methods has been successful and well documented. In comparison the ability to measure logP for surfactants is considered impractical due to their amphiphilic nature, which gives them a tendency to form micelles and reside at the octanol-water interface. In this study we have shown that working with compounds below their critical micelle concentrations (CMC), at the experimental concentrations, it is possible to obtain experimental logP values for a series of sulphobetaines using the stir-flask method coupled with reversed phase-high performance liquid chromatography (RP-HPLC). Until now the ability to verify calculated logP values for surfactants has been limited. Measuring logP as described here can now be applied to other surfactants to validate existing and new modifications to the fragment method.

In silico prediction of aqueous solubility: the solubility challenge.

The dissolution of a chemical into water is a process fundamental to both chemistry and biology. The persistence of a chemical within the environment and the effects of a chemical within the body are dependent primarily upon aqueous solubility. With the well-documented limitations hindering the accurate experimental determination of aqueous solubility, the utilization of predictive methods have been widely investigated and employed. The setting of a solubility challenge by this journal proved an excellent opportunity to explore several different modeling methods, utilizing a supplied dataset of high-quality aqueous solubility measurements. Four contrasting approaches (simple linear regression, artificial neural networks, category formation, and available in silico models) were utilized within our laboratory and the quality of these predictions was assessed. These were chosen to span the multitude of modeling methods now in use, while also allowing for the evaluation of existing commercial solubility models. The conclusions of this study were surprising, in that a simple linear regression approach proved to be superior over more complex modeling methods. Possible explanations for this observation are discussed and also recommendations are made for future solubility prediction.

Genetic diversity among Brazilian isolates of Beauveria bassiana: comparisons with non-Brazilian isolates and other Beauveria species.

AIMS: The genetic diversity of Beauveria bassiana was investigated by comparing isolates of this species to each other (49 from different geographical regions of Brazil and 4 from USA) and to other Beauveria spp. METHODS AND RESULTS: The isolates were examined by multilocus enzyme electrophoresis (MLEE), amplified fragment length polymorphism (AFLP), and rDNA sequencing. MLEE and AFLP revealed considerable genetic variability among B. bassiana isolates. Several isolates from South and Southeast Brazil had high similarity coefficients, providing evidence of at least one population with clonal structure. There were clear genomic differences between most Brazilian and USA B. bassiana isolates. A Mantel test using data generated by AFLP provided evidence that greater geographical distances were associated with higher genetic distances. AFLP and rDNA sequencing demonstrated notable genotypic variation between B. bassiana and other Beauveria spp. CONCLUSION: Geographical distance between populations apparently is an important factor influencing genotypic variability among B. bassiana populations in Brazil. SIGNIFICANCE AND IMPACT OF THE STUDY: This study characterized many B. bassiana isolates. The results indicate that certain Brazilian isolates are considerably different from others and possibly should be regarded as separate species from B. bassiana sensu latu. The information on genetic variation among the Brazilian isolates, therefore, will be important to comprehending the population structure of B. bassiana in Brazil.

Asthma as a predictor of obstructive sleep apnea in urban African-American children.

BACKGROUND: Asthma is a known co-morbid factor in childhood obstructive sleep apnea (OSA); however, little is known about the effects that asthma might have on the severity of OSA. We hypothesize that children with concomitant asthma and OSA have more severe OSA. METHODS: We conducted a prospective study of 50 children with OSA diagnosed by polysomnography referred for tonsillectomy and adenoidectomy (T&A). The presence of concomitant asthma was determined by ISAAC questionnaire and spirometry. Atopy to common allergens was determined by skin prick testing. Due to the relatively small sample size, we limited hypothesis testing to cross tabulations with Fisher's Exact Test and t testing. We also employed a parsimonious ordinary least squares (OLS) regression assuming a large effect size. RESULTS: Subjects (n = 50) included 32 males and 41 African-Americans. Age at T&A was 9.3 +/- 3.4 years (mean +/- S.D). Thirty-two subjects reported a history of asthma during their lifetimes, but the ISAAC questionnaire detected only 30 subjects. Twenty-two subjects reported current asthma. Atopy was found in 27 subjects. Apnea-hypopnea index (AHI) was lower in the current asthma group than in the lifetime asthma group but did not reach statistical significance. However, AHI was significantly higher in subjects with poorly controlled asthma. Further, in a parsimonious OLS model controlling for sleep efficiency and age, a history of lifetime asthma increased the AHI by 8.8 (p < 0.05). DISCUSSION: In urban African-American children referred for T&A to treat OSA, a history of poorly controlled asthma is associated with more severe OSA.

Neutron Rem Detector Response Changes due to Activation of Components.

The relative response of neutron rem detectors has previously been shown to increase after prolonged exposure to a neutron flux. This increase has been referred to as the "soak factor." The cause of the increased response has been previously unexplained. This note reports on a search for the underlying cause of the increased response. Testing involved gamma-ray spectroscopy of activated neutron rem detector components and testing of instrument response at various rates of neutron flux and accumulated fluence. The proposed primary cause of the increased response is activation of copper in the brass collar at the fill end of the gas-filled detector tube. This component allows for attachment of the extension housing on the tube containing BF3 or He gas. Under a neutron flux, some of this copper activates to Cu. In addition, Mn was detected in activated components but does not seem to be a significant contributor to the detector response. Cadmium isotopes did not appear to be significant. The activated component causes an increase in indicated neutron dose rate due to decay photons from activated components. Photons normally have little impact on neutron rem detector readings because the electrical pulses produced in the probes are below the lower-level discriminator. However, the photon pulses do impact the overall count rate when they occur simultaneously with normally uncounted, lower amplitude, wall-effect neutron pulses.

An evaluation of selected (Q)SARs/expert systems for predicting skin sensitisation potential.

Predictive testing to characterise substances for their skin sensitisation potential has historically been based on animal models such as the Local Lymph Node Assay (LLNA) and the Guinea Pig Maximisation Test (GPMT). In recent years, EU regulations, have provided a strong incentive to develop non-animal alternatives, such as expert systems software. Here we selected three different types of expert systems: VEGA (statistical), Derek Nexus (knowledge-based) and TIMES-SS (hybrid), and evaluated their performance using two large sets of animal data: one set of 1249 substances from eChemportal and a second set of 515 substances from NICEATM. A model was considered successful at predicting skin sensitisation potential if it had at least the same balanced accuracy as the LLNA and the GPMT had in predicting the other outcomes, which ranged from 79% to 86%. We found that the highest balanced accuracy of any of the expert systems evaluated was 65% when making global predictions. For substances within the domain of TIMES-SS, however, balanced accuracies for the two datasets were found to be 79% and 82%. In those cases where a chemical was within the TIMES-SS domain, the TIMES-SS skin sensitisation hazard prediction had the same confidence as the result from LLNA or GPMT.