Highly potent delivery method of gp160 envelope vaccine combining lentivirus-like particles and DNA electrotransfer

Particulate antigen assemblies in the nanometer range and DNA plasmids are particularly interesting for designing vaccines. We hypothesised that a combination of these approaches could result in a new delivery method of gp160 envelope HIV-1 vaccine which could combine the potency of virus-like particles (VLPs) and the simplicity of use of DNA vaccines. Characterisation of lentivirus-like particles (lentiVLPs) by western blot, dynamic light scattering and electron microscopy revealed that their protein pattern, size and structure make them promising candidates for HIV-1 vaccines. Although all particles were similar with regard to size and distribution, they clearly differed in p24 capsid protein content suggesting that Rev may be required for particle maturation and Gag processing. In vivo, lentiVLP pseudotyping with the gp160 envelope or with a combination of gp160 and VSV-G envelopes did not influence the magnitude of the immune response but the combination of lentiVLPs with Alum adjuvant resulted in a more potent response. Interestingly, the strongest immune response was obtained when plasmids encoding lentiVLPs were co-delivered to mice muscles by electrotransfer, suggesting that lentiVLPs were efficiently produced in vivo or the packaging genes mediate an adjuvant effect. DNA electrotransfer of plasmids encoding lentivirus-like particles offers many advantages and appears therefore as a promising delivery method of HIV-1 vaccines. Keywords:VLP, Electroporation, Electrotransfer, HIV vaccine, DNA vaccine

Causal relationship between obesity and vitamin D status: bi-directional mendelian randomization analysis of multiple cohorts

BACKGROUND: Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional Mendelian randomization (MR) analysis. METHODS AND FINDINGS: We used information from 21 adult cohorts (up to 42,024 participants) with 12 BMI-related SNPs (combined in an allelic score) to produce an instrument for BMI and four SNPs associated with 25(OH)D (combined in two allelic scores, separately for genes encoding its synthesis or metabolism) as an instrument for vitamin D. Regression estimates for the IVs (allele scores) were generated within-study and pooled by meta-analysis to generate summary effects. Associations between vitamin D scores and BMI were confirmed in the Genetic Investigation of Anthropometric Traits (GIANT) consortium (n = 123,864). Each 1 kg/m(2) higher BMI was associated with 1.15% lower 25(OH)D (p = 6.52×10⁻²⁷). The BMI allele score was associated both with BMI (p = 6.30×10⁻⁶²) and 25(OH)D (-0.06% [95% CI -0.10 to -0.02], p = 0.004) in the cohorts that underwent meta-analysis. The two vitamin D allele scores were strongly associated with 25(OH)D (p≤8.07×10⁻⁵⁷ for both scores) but not with BMI (synthesis score, p = 0.88; metabolism score, p = 0.08) in the meta-analysis. A 10% higher genetically instrumented BMI was associated with 4.2% lower 25(OH)D concentrations (IV ratio: -4.2 [95% CI -7.1 to -1.3], p = 0.005). No association was seen for genetically instrumented 25(OH)D with BMI, a finding that was confirmed using data from the GIANT consortium (p≥0.57 for both vitamin D scores). CONCLUSIONS: On the basis of a bi-directional genetic approach that limits confounding, our study suggests that a higher BMI leads to lower 25(OH)D, while any effects of lower 25(OH)D increasing BMI are likely to be small. Population level interventions to reduce BMI are expected to decrease the prevalence of vitamin D deficiency.

Method of determining a geophysical-scale sea ice rheology from laboratory measurements

We present a methodology that allows a sea ice rheology, suitable for use in a General Circulation Model (GCM), to be determined from laboratory and tank experiments on sea ice when combined with a kinematic model of deformation. The laboratory experiments determine a material rheology for sea ice, and would investigate a nonlinear friction law of the form τ ∝ σ n⅔, instead of the more familiar Amonton's law, τ = μσn (τ is the shear stress, μ is the coefficient of friction and σ n is the normal stress). The modelling approach considers a representative region R containing ice floes (or floe aggregates), separated by flaws. The deformation of R is imposed and the motion of the floes determined using a kinematic model, which will be motivated from SAR observations. Deformation of the flaws is inferred from the floe motion and stress determined from the material rheology. The stress over R is then determined from the area-weighted contribution from flaws and floes

Survival analysis statistics applied to threshold data obtained from the ascending forced-choice method of limits

Sensory thresholds are often collected through ascending forced-choice methods. Group thresholds are important for comparing stimuli or populations; yet, the method has two problems. An individual may correctly guess the correct answer at any concentration step and might detect correctly at low concentrations but become adapted or fatigued at higher concentrations. The survival analysis method deals with both issues. Individual sequences of incorrect and correct answers are adjusted, taking into account the group performance at each concentration. The technique reduces the chance probability where there are consecutive correct answers. Adjusted sequences are submitted to survival analysis to determine group thresholds. The technique was applied to an aroma threshold and a taste threshold study. It resulted in group thresholds similar to ASTM or logarithmic regression procedures. Significant differences in taste thresholds between younger and older adults were determined. The approach provides a more robust technique over previous estimation methods.

Folding of graphene slit like pore walls—a simple method of improving CO2 separation from mixtures with CH4 or N2

We report for the first time a detailed procedure for creating a simulation model of energetically stable, folded graphene-like pores and simulation results of CO2/CH4 and CO2/N2 separation using these structures. We show that folding of graphene structures is a very promising method to improve the separation of CO2 from mixtures with CH4 and N2. The separation properties of the analyzed materials are compared with carbon nanotubes having similar diameters or S/V ratio. The presented results have potential importance in the field of CO2 capture and sequestration.

The Maunder minimum (1645-1715) was indeed a grand minimum: a reassessment of multiple datasets

Aims. Although the time of the Maunder minimum (1645–1715) is widely known as a period of extremely low solar activity, it is still being debated whether solar activity during that period might have been moderate or even higher than the current solar cycle (number 24). We have revisited all existing evidence and datasets, both direct and indirect, to assess the level of solar activity during the Maunder minimum. Methods. We discuss the East Asian naked-eye sunspot observations, the telescopic solar observations, the fraction of sunspot active days, the latitudinal extent of sunspot positions, auroral sightings at high latitudes, cosmogenic radionuclide data as well as solar eclipse observations for that period. We also consider peculiar features of the Sun (very strong hemispheric asymmetry of the sunspot location, unusual differential rotation and the lack of the K-corona) that imply a special mode of solar activity during the Maunder minimum. Results. The level of solar activity during the Maunder minimum is reassessed on the basis of all available datasets. Conclusions. We conclude that solar activity was indeed at an exceptionally low level during the Maunder minimum. Although the exact level is still unclear, it was definitely lower than during the Dalton minimum of around 1800 and significantly below that of the current solar cycle #24. Claims of a moderate-to-high level of solar activity during the Maunder minimum are rejected with a high confidence level.

Stimulation of multiple mitogen-activated protein kinase sub-families by oxidative stress and phosphorylation of the small heat shock protein, HSP25/27, in neonatal ventricular myocytes.

We investigated the activation of three subfamilies of mitogen-activated protein kinases (MAPKs), namely the stress-activated protein kinases/c-Jun N-terminal kinases (SAPKs/JNKs), the extracellularly responsive kinases (ERKs) and p38-MAPK, by oxidative stress as exemplified by H2O2 in primary cultures of neonatal rat ventricular myocytes. The 46 and 54 kDa species of SAPKs/JNKs were activated 5- and 10-fold, respectively, by 0.1 mM H2O2 (the maximally effective concentration). Maximal activation occurred at 15-30 min, but was still detectable after 2 h. Both ERK1 and ERK2 were activated 16-fold by 0.1 mM H2O2 with a similar time course to the SAPKs/JNKs, and this was comparable with their activation by 1 microM PMA, the most powerful activator of ERKs that we have so far identified in these cells. The activation of ERKs by H2O2 was inhibited by PD98059, which inhibits the activation of MAPK (or ERK) kinases, and by the protein kinase C (PKC) inhibitor, GF109203X. ERK activation was also inhibited by down-regulation of PMA-sensitive PKC isoforms. p38-MAPK was activated by 0.1 mM H2O2 as shown by an increase in its phosphorylation. However, maximal phosphorylation (activation) was more rapid (<5 min) than for the SAPKs/JNKs or the ERKs. We studied the downstream consequences of p38-MAPK activation by examining activation of MAPK-activated protein kinase 2 (MAPKAPK2) and phosphorylation of the MAPKAPK2 substrate, the small heat shock protein HSP25/27. As with p38-MAPK, MAPKAPK2 was rapidly activated (maximal within 5 min) by 0.1 mM H2O2. This activation was abolished by 10 microM SB203580, a selective inhibitor of certain p38-MAPK isoforms. The phosphorylation of HSP25/27 rapidly followed activation of MAPKAPK2 and was also inhibited by SB203580. Phosphorylation of HSP25/27 was associated with a decrease in its aggregation state. These data indicate that oxidative stress is a powerful activator of all three MAPK subfamilies in neonatal rat ventricular myocytes. Activation of all three MAPKs has been associated with the development of the hypertrophic phenotype. However, stimulation of p38-MAPK and the consequent phosphorylation of HSP25/27 may also be important in cardioprotection.

A method of evaluating the accuracy of human body thermoregulation models

Human Body Thermoregulation Models have been widely used in the field of human physiology or thermal comfort studies. However there are few studies on the evaluation method for these models. This paper summarises the existing evaluation methods and critically analyses the flaws. Based on that, a method for the evaluating the accuracy of the Human Body Thermoregulation models is proposed. The new evaluation method contributes to the development of Human Body Thermoregulation models and validates their accuracy both statistically and empirically. The accuracy of different models can be compared by the new method. Furthermore, the new method is not only suitable for the evaluation of Human Body Thermoregulation Models, but also can be theoretically applied to the evaluation of the accuracy of the population-based models in other research fields.

A systematic method of parameterisation estimation using data assimilation

In numerical weather prediction, parameterisations are used to simulate missing physics in the model. These can be due to a lack of scientific understanding or a lack of computing power available to address all the known physical processes. Parameterisations are sources of large uncertainty in a model as parameter values used in these parameterisations cannot be measured directly and hence are often not well known; and the parameterisations themselves are also approximations of the processes present in the true atmosphere. Whilst there are many efficient and effective methods for combined state/parameter estimation in data assimilation (DA), such as state augmentation, these are not effective at estimating the structure of parameterisations. A new method of parameterisation estimation is proposed that uses sequential DA methods to estimate errors in the numerical models at each space-time point for each model equation. These errors are then fitted to pre-determined functional forms of missing physics or parameterisations that are based upon prior information. We applied the method to a one-dimensional advection model with additive model error, and it is shown that the method can accurately estimate parameterisations, with consistent error estimates. Furthermore, it is shown how the method depends on the quality of the DA results. The results indicate that this new method is a powerful tool in systematic model improvement.

Estrogen receptor-mediated transcription involves the activation of multiple kinase pathways in neuroblastoma cells

While many physiological effects of estrogens (E) are due to regulation of gene transcription by liganded estrogen receptors (ERs), several effects are also mediated, at least in part, by rapid non-genomic actions of E. Though the relative importance of rapid versus genomic effects in the central nervous system is controversial, we showed previously that membrane-limited effects of E, initiated by an estradiol bovine serum albumin conjugate (E2-BSA), could potentiate transcriptional effects of 17beta-estradiol from an estrogen response element (ERE)-reporter in neuroblastoma cells. Here, using specific inhibitors and activators in a pharmacological approach, we show that activation of phosphatidylinositol-3-phosphate kinase (PI3K) and mitogen activated protein kinase (MAPK) pathways, dependent on a Galphaq coupled receptor signaling are important in this transcriptional potentiation. We further demonstrate, using ERalpha phospho-deficient mutants, that E2-BSA mediated phosphorylation of ERalpha is one mechanism to potentiate transcription from an ERE reporter construct. This study provides a possible mechanism by which signaling from the membrane is coupled to transcription in the nucleus, providing an integrated view of hormone signaling in the brain.

Does fertilizer type and method of application cause significant differences in essential oil yield and composition in rosemary (Rosmarinus officinalis L.)?

Organic fertilizers based on seaweed extract potentially have beneficial effects on many crop plants. Herewe investigate the impact of organic fertilizer on Rosmarinus officinalis measured by both yield and oilquality. Plants grown in a temperature-controlled greenhouse with a natural photoperiod and a controlledirrigation system were treated with seaweed fertilizer and an inorganic fertilizer of matching mineralcomposition but with no organic content. Treatments were either by spraying on to the foliage or wateringdirect to the compost. The essential oil was extracted by hydro-distillation with a Clevenger apparatusand analysed by gas-chromatography mass-spectrometry (GC–MS) and NMR. The chemical composi-tions of the plants were compared, and qualitative differences were found between fertilizer treatmentsand application methods. Thus sprayed seaweed fertilizer showed a significantly higher percentage of�-pinene, �-phellandrene, �-terpinene (monoterpenes) and 3-methylenecycloheptene than other treat-ments. Italicene, �-bisabolol (sesquiterpenes), �-thujene, and E-isocitral (monoterpenes) occurred insignificantly higher percentages for plants watered with the seaweed extract. Each was significantly dif-ferent to the inorganic fertilizer and to controls. The seaweed treatments caused a significant increasein oil amount and leaf area as compared with both inorganic treatments and the control regardless ofapplication method.

A constrained recursive least squares algorithm for adaptive combination of multiple models

In this paper, we develop a novel constrained recursive least squares algorithm for adaptively combining a set of given multiple models. With data available in an online fashion, the linear combination coefficients of submodels are adapted via the proposed algorithm.We propose to minimize the mean square error with a forgetting factor, and apply the sum to one constraint to the combination parameters. Moreover an l1-norm constraint to the combination parameters is also applied with the aim to achieve sparsity of multiple models so that only a subset of models may be selected into the final model. Then a weighted l2-norm is applied as an approximation to the l1-norm term. As such at each time step, a closed solution of the model combination parameters is available. The contribution of this paper is to derive the proposed constrained recursive least squares algorithm that is computational efficient by exploiting matrix theory. The effectiveness of the approach has been demonstrated using both simulated and real time series examples.