Reducing Bias and Quantifying Uncertainty in Fluorescence Produced by PCR.

We present a new approach for relating nucleic-acid content to fluorescence in a real-time Polymerase Chain Reaction (PCR) assay. By coupling a two-type branching process for PCR with a fluorescence analog of Beer's Law, the approach reduces bias and quantifies uncertainty in fluorescence. As the two-type branching process distinguishes between complementary strands of DNA, it allows for a stoichiometric description of reactions between fluorescent probes and DNA and can capture the initial conditions encountered in assays targeting RNA.

Binding, brightness, or noise? Extracting temperature-dependent properties of dye bound to DNA.

We present a method for extracting temperature-dependent thermodynamic and photophysical properties of SYTO-13 dye bound to DNA from fluorescence measurements. Together, mathematical modeling, control experiments, and numerical optimization enable dye binding strength, dye brightness, and experimental noise (or error) to be discriminated from one another. By focusing on the low-dye-coverage regime, the model avoids bias and can simplify quantification.

Fingerprinting diverse nanoporous materials for optimal hydrogen storage conditions using meta-learning.

Adsorptive hydrogen storage is a desirable technology for fuel cell vehicles, and efficiently identifying the optimal storage temperature requires modeling hydrogen loading as a continuous function of pressure and temperature. Using data obtained from high-throughput Monte Carlo simulations for zeolites, metal-organic frameworks, and hyper-cross-linked polymers, we develop a meta-learning model that jointly predicts the adsorption loading for multiple materials over wide ranges of pressure and temperature. Meta-learning gives higher accuracy and improved generalization compared to fitting a model separately to each material and allows us to identify the optimal hydrogen storage temperature with the highest working capacity for a given pressure difference.

Deep neural network learning of complex binary sorption equilibria from molecular simulation data.

We employed deep neural networks (NNs) as an efficient and intelligent surrogate of molecular simulations for complex sorption equilibria using probabilistic modeling. Canonical ( ) Gibbs ensemble Monte Carlo simulations were performed to model a single-stage equilibrium desorptive drying process for (1,4-butanediol or 1,5-pentanediol)/water and 1,5-pentanediol/ethanol from all-silica MFI zeolite and 1,5-pentanediol/water from all-silica LTA zeolite. A multi-task deep NN was trained on the simulation data to predict equilibrium loadings as a function of thermodynamic state variables.

Vapor- and Liquid-Phase Adsorption of Alcohol and Water in Silicalite-1 Synthesized in Fluoride Media.

In this work, batch-adsorption experiments and molecular simulations are employed to probe the adsorption of binary mixtures containing ethanol or a linear alkane-1,n-diol solvated in water or ethanol onto silicate-1. Since the batch-adsorption experiments require an additional relationship to determine the amount of solute (and solvent adsorbed, as only the bulk liquid reservoir can be probed directly, molecular simulations are used to provide a relationship between solute and solvent adsorption for input to the experimental bulk measurements. The combination of bulk experimental measurements and simulated solute-solvent relationship yields solvent and solute loadings that are self-consistent with simulation alone, and allow for an assessment of the various assumptions made in literature.

Understanding the unique sorption of alkane-, -diols in silicalite-1.

Adsorption equilibria of alkane-, -diols (propane-1,3-diol, butane-1,4-diol, pentane-1,5-diol, and hexane-1,6-diol) from aqueous solution onto an all-silica zeolite of the type mordenite framework inverted (MFI, also known as silicalite-1) are obtained by simulations and experiments at = 323 K and also for pentane-1,5-diol (C5) at 348 and 383 K. After an initial slow rise, isotherms at = 323 K exhibit steep changes in loading, reaching saturation at 10, 9, 8, and 7 molec/uc as the number of carbon atoms of the diols increases from 3 to 6. The abrupt change in loading corresponds to a minimum in the free energy of adsorption (from vapor to zeolite) that is associated with a rapid rise in the number of hydrogen bonds per sorbate molecule due to the formation of large clusters.

Comparative Study of the Effect of Defects on Selective Adsorption of Butanol from Butanol/Water Binary Vapor Mixtures in Silicalite-1 Films.

A promising route for sustainable 1-butanol (butanol) production is ABE (acetone, butanol, ethanol) fermentation. However, recovery of the products is challenging because of the low concentrations obtained in the aqueous solution, thus hampering large-scale production of biobutanol. Membrane and adsorbent-based technologies using hydrophobic zeolites are interesting alternatives to traditional separation techniques (e.

A Review of Biorefinery Separations for Bioproduct Production via Thermocatalytic Processing.

With technological advancement of thermocatalytic processes for valorizing renewable biomass carbon, development of effective separation technologies for selective recovery of bioproducts from complex reaction media and their purification becomes essential. The high thermal sensitivity of biomass intermediates and their low volatility and high reactivity, along with the use of dilute solutions, make the bioproducts separations energy intensive and expensive. Novel separation techniques, including solvent extraction in biphasic systems and reactive adsorption using zeolite and carbon sorbents, membranes, and chromatography, have been developed.

Ultra-selective high-flux membranes from directly synthesized zeolite nanosheets.

A zeolite with structure type MFI is an aluminosilicate or silicate material that has a three-dimensionally connected pore network, which enables molecular recognition in the size range 0.5-0.6 nm.

Adsorptive Separation of 1-Butanol from Aqueous Solutions Using MFI- and FER-Type Zeolite Frameworks: A Monte Carlo Study.

Anaerobic fermentation can transform carbohydrates to yield a multicomponent mixture comprising mainly of acetone, 1-butanol, and ethanol (ABE) in a typical weight ratio of 3:6:1. Compared to ethanol, 1-butanol, the main product of ABE fermentation, offers significant advantages as a biofuel or a fuel additive. However, the toxicity of 1-butanol for cell cultures requires broth concentrations to be low in 1-butanol (≈1-2 wt %).

[Chronic subdural hematoma in aged patients. Diagnostic problems].

The history, clinical features, laboratory tests and admission circumstances were analysed retrospectively in 14 patients, aged 60 to 87 years, who were found to have a chronic subdural haematoma. Typical clinical features consisted of dominant psychiatric disorders, slow progression and frequently only traces of neurological signs. In only four patients was headache the initial symptom.

[Etiology of cerebral infarcts caused by emboli--subacute bacterial endocarditis].

Bacterial endocarditis is a rare cause of brain infarction. Prediposing factors are frequently valvular defects secondary to rheumatic conditions. A slowly progressive course and atypical symptoms of the disease can mask the condition to such an extent that the correct diagnosis is obtained only through the work up of secondary embolic complications.

[The anterior tibial syndrome (author's transl)].

The anterior tibial syndrome is caused by primary or secondary ischemia of the tibial muscles group. Acute onset of intensive pain, swelling of the muscles and reddening of the skin are the clinical features of the syndrome. The muscles enzymes are raised.