Detection limits of organic compounds achievable with intense, short-pulse lasers

Many organic molecules have strong absorption bands which can be accessed by ultraviolet short pulse lasers to produce efficient ionization. This resonant multiphoton ionization scheme has already been exploited as an ionization source in time-of-flight mass spectrometers used for environmental trace analysis. In the present work we quantify the ultimate potential of this technique by measuring absolute ion yields produced from the interaction of 267 nm femtosecond laser pulses with the organic molecules indole and toluene, and gases Xe, N2 and O2. Using multiphoton ionization cross sections extracted from these results, we show that the laser pulse parameters required for real-time detection of aromatic molecules at concentrations of one part per trillion in air and a limit of detection of a few attomoles are achievable with presently available commercial laser systems. The potential applications for the analysis of human breath, blood and tissue samples are discussed

An Exponential Reduction in Training Data Sizes for Machine Learning Derived Entanglement Witnesses

We propose a support vector machine (SVM) based approach for generating an entanglement witness that requires exponentially less training data than previously proposed methods. SVMs generate hyperplanes represented by a weighted sum of expectation values of local observables whose coefficients are optimized to sum to a positive number for all separable states and a negative number for as many entangled states as possible near a specific target state. Previous SVM-based approaches for entanglement witness generation used large amounts of randomly generated separable states to perform training, a task with considerable computational overhead. Here, we propose a method for orienting the witness hyperplane using only the significantly smaller set of states consisting of the eigenstates of the generalized Pauli matrices and a set of entangled states near the target entangled states. With the orientation of the witness hyperplane set by the SVM, we tune the plane's placement using a differential program that ensures perfect classification accuracy on a limited test set as well as maximal noise tolerance. For $N$ qubits, the SVM portion of this approach requires only $O(6^N)$ training states, whereas an existing method needs $O(2^{4^N})$. We use this method to construct witnesses of 4 and 5 qubit GHZ states with coefficients agreeing with stabilizer formalism witnesses to within 6.5 percent and 1 percent, respectively. We also use the same training states to generate novel 4 and 5 qubit W state witnesses. Finally, we computationally verify these witnesses on small test sets and propose methods for further verification.Comment: 22 Pages, 3 Figure

Impact of intermittent preventive anti-malarial treatment on the growth and nutritional status of preschool children in rural Senegal (west Africa).

Negative consequences of malaria might account for seasonality in nutritional status in children in the Sahel. We report the impact of a randomized, double-blind, placebo-controlled trial of seasonal intermittent preventive anti-malarial treatment on growth and nutritional status in 1,063 Senegalese preschool children. A combination of artesunate and sulfadoxine-pyrimethamine was given monthly from September to November. In the intervention arm, mean weight gain was significantly greater (122.9 +/- 340 versus 42.9 +/- 344 [SD] g/mo, P < 0.0001) and losses in triceps and subscapular skinfold measurements were less (-0.39 +/- 1.01 versus -0.66 +/- 1.01 mm/mo, and -0.15 +/- 0.64 versus -0.36 +/- 0.62 mm/mo, respectively, P < 0.0001 for both). There was no difference in height increments. The prevalence of wasting increased significantly in the control arm (4.6% before versus 9.5% after, P < 0.0001), but remained constant in intervention children: 5.6% versus 7.0% (P = 0.62). The prevention of malaria would improve child nutritional status in areas with seasonal transmission

Direct evidence of lack of colocalisation of fluorescently labelled gold labels used in correlative light electron microscopy

Fluorescently labelled nanoparticles are routinely used in Correlative Light Electron Microscopy (CLEM) to combine the capabilities of two separate microscope platforms: fluorescent light microscopy (LM) and electron microscopy (EM). The inherent assumption is that the fluorescent label observed under LM colocalises well with the electron dense nanoparticle observed in EM. Herein we show, by combining single molecule fluorescent imaging with optical detection of the scattering from single gold nanoparticles, that for a commercially produced sample of 10 nm gold nanoparticles tagged to Alexa-633 there is in fact no colocalisation between the fluorescent signatures of Alexa-633 and the scattering associated with the gold nanoparticle. This shows that the attached gold nanoparticle quenches the fluorescent signal by ~95%, or less likely that the complex has dissociated. In either scenario, the observed fluorescent signal in fact arises from a large population of untagged fluorophores; rendering these labels potentially ineffective and misleading to the field

Anti-malarial drugs and the prevention of malaria in the population of malaria endemic areas

Anti-malarial drugs can make a significant contribution to the control of malaria in endemic areas when used for prevention as well as for treatment. Chemoprophylaxis is effective in preventing deaths and morbidity from malaria, but it is difficult to sustain for prolonged periods, may interfere with the development of naturally acquired immunity and will facilitate the emergence and spread of drug resistant strains if applied to a whole community. However, chemoprophylaxis targeted to groups at high risk, such as pregnant women, or to periods of the year when the risk from malaria is greatest, can be an effective and cost effective malaria control tool and has fewer drawbacks. Intermittent preventive treatment, which involves administration of anti-malarials at fixed time points, usually when a subject is already in contact with the health services, for example attendance at an antenatal or vaccination clinic, is less demanding of resources than chemoprophylaxis and is now recommended for the prevention of malaria in pregnant women and infants resident in areas with medium or high levels of malaria transmission. Intermittent preventive treatment in older children, probably equivalent to targeted chemoprophylaxis, is also highly effective but requires the establishment of a specific delivery system. Recent studies have shown that community volunteers can effectively fill this role. Mass drug administration probably has little role to play in control of mortality and morbidity from malaria but may have an important role in the final stages of an elimination campaign

Multifractal characterization of stochastic resonance

We use a multifractal formalism to study the effect of stochastic resonance in a noisy bistable system driven by various input signals. To characterize the response of a stochastic bistable system we introduce a new measure based on the calculation of a singularity spectrum for a return time sequence. We use wavelet transform modulus maxima method for the singularity spectrum computations. It is shown that the degree of multifractality defined as a width of singularity spectrum can be successfully used as a measure of complexity both in the case of periodic and aperiodic (stochastic or chaotic) input signals. We show that in the case of periodic driving force singularity spectrum can change its structure qualitatively becoming monofractal in the regime of stochastic synchronization. This fact allows us to consider the degree of multifractality as a new measure of stochastic synchronization also. Moreover, our calculations have shown that the effect of stochastic resonance can be catched by this measure even from a very short return time sequence. We use also the proposed approach to characterize the noise-enhanced dynamics of a coupled stochastic neurons model.Comment: 10 pages, 21 EPS-figures, RevTe

Modelling the impact of intermittent preventive treatment for malaria on selection pressure for drug resistance

BACKGROUND: Intermittent preventive treatment (IPT) is a promising intervention for malaria control, although there are concerns about its impact on drug resistance. METHODS: The key model inputs are age-specific values for a) baseline anti-malarial dosing rate, b) parasite prevalence, and c) proportion of those treated with anti-malarials (outside IPT) who are infected. These are used to estimate the immediate effect of IPT on the genetic coefficient of selection (s). The scenarios modelled were year round IPT to infants in rural southern Tanzania, and three doses at monthly intervals of seasonal IPT in Senegal. RESULTS: In the simulated Tanzanian setting, the model suggests a high selection pressure for drug resistance, but that IPTi would only increase this by a small amount (4.4%). The percent change in s is larger if parasites are more concentrated in infants, or if baseline drug dosing is less common or less specific. If children aged up to five years are included in the Tanzanian scenario then the predicted increase in s rises to 31%. The Senegalese seasonal IPT scenario, in children up to five years, results in a predicted increase in s of 16%. CONCLUSION: There is a risk that the useful life of drugs will be shortened if IPT is implemented over a wide childhood age range. On the other hand, IPT delivered only to infants is unlikely to appreciably shorten the useful life of the drug used

Genome-wide association study identifies 30 loci associated with bipolar disorder.

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P &lt; 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P &lt; 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder