A comparison of methods for sample size estimation for non-inferiority studies with binary outcomes

Non-inferiority trials are motivated in the context of clinical research where a proven active treatment exists and placebo-controlled trials are no longer acceptable for ethical reasons. Instead, active-controlled trials are conducted where a treatment is compared to an established treatment with the objective of demonstrating that it is non-inferior to this treatment. We review and compare the methodologies for calculating sample sizes and suggest appropriate methods to use. We demonstrate how the simplest method of using the anticipated response is predominantly consistent with simulations. In the context of trials with binary outcomes with expected high proportions of positive responses, we show how the sample size is quite sensitive to assumptions about the control response. We recommend when designing such a study that sensitivity analyses be performed with respect to the underlying assumptions and that the Bayesian methods described in this article be adopted to assess sample size.     

Methods and models for the risk analysis and security management of chemical plants

The theoretical foundations for the risk analysis and assessment and the security management of chemical plants are elaborated. Logical graphical, logical, and probabilistic models for the analysis and assessment of the risk of accident occurrence for different types of chemically hazardous objects are proposed. The classification of the problems of the security management of chemical plants is conducted and production models for the operative security management of chemica technology systems intended to prevent the appearance of failures and emergencies in the units of chemical plants are developed. Examples of the practical application of the models and methods for the analysis of the occupational hazards, risk assessment, and security management of chemical and oil refining plants are presented.     

Machine learning models for the density and heat capacity of ionic liquid-water binary mixtures

Ionic liquids（ILs）, because of the advantages of low volatility, good thermal stability, high gas solubility and easy recovery, can be regarded as the green substitute for traditional solvent. However, the high viscosity and synthesis cost limits their application, the hybrid solvent which combining ILs together with others especially water can solve this problem. Compared with the pure IL systems, the study of the ILs-H₂O binary system is rare, and the experimental data of corresponding thermodynamic properties（such as density, heat capacity, etc.） are less. Moreover, it is also difficult to obtain all the data through experiments. Therefore, this work establishes a predicted model on ILs-water binary systems based on the group contribution（GC） method. Three different machine learning algorithms（ANN, XGBoost,LightBGM） are applied to fit the density and heat capacity of ILs-water binary systems. And then the three models are compared by two index of MAE and R². The results show that the ANN-GC model has the best prediction effect on the density and heat capacity of ionic liquid-water mixed system.Furthermore, the Shapley additive explanations（SHAP） method is harnessed to scrutinize the significance of each structure and parameter within the ANN-GC model in relation to prediction outcomes. The results reveal that system components(X_IL) within the ILs-H₂O binary system exert the most substantial influence on density, while for the heat capacity, the substituents on the cation exhibit the greatest impact. This study not only introduces a robust prediction model for the density and heat capacity properties of IL-H₂O binary mixtures but also provides insight into the influence of mixture features on its density and heat capacity.     

Review of analytical methods for prospective cohort studies using time to event data: single studies and implications for meta-analysis

Prospective cohort studies are extremely important in epidemiological research as they give direct information on the sequence of events, which can be used to demonstrate causality. They also have the advantage that many diseases can be studied simultaneously. However, they are usually very time consuming and expensive to run. In addition, practitioners of evidence-based medicine prefer to make decisions based on several studies rather than a single study, hence the need for meta-analysis. The use of meta-analyses in order to synthesize the evidence from randomized controlled trials is extremely popular in medicine and is also being utilized increasingly in epidemiology. The statistical methodology for meta-analyses of epidemiological studies is a long way behind in terms of the advances made in the methodology for randomized controlled trials. Numerous methodological issues, particularly in respect to dealing with biases inherent in these types of studies, have made the results of meta-analyses of epidemiological studies that use summary data open to criticism. This review mainly concentrates on analytical methods for prospective cohort studies that have survival outcomes. In addition, the implications for meta-analysis assuming that the analyst has access to individual participant data are also discussed. The approaches are described with respect to underlying theory and assumptions. It is hoped that this review will promote the use of these approaches in meta-analyses conducted in epidemiology as well as providing some directions for future research.     

A comparative study for nanoparticle production with passive mixers via solvent-displacement: Use of CFD models for optimization and design

Active and passive mixers, including a considerable variety of micro-devices, are nowadays widely used for the production of nanoparticles. Polymer nanoparticles for controlled drug delivery applications are investigated in this work with two specific objectives. The first one is to experimentally quantify the efficiency of confined impinging jets reactors and Tee-mixers in the production of nanoparticles constituted by two polymers: poly-?-caprolactone and poly(methoxypolyethyleneglycolcyanoacrylate-co-hexadecylcyanoacrylate). The second objective is the development of a simple and reliable mathematical model to be used for the design, optimization and scale up of mixers for polymer nanoparticle production. Although the behaviour of the polymers investigated is quite different, it is possible to conclude that confined impinging jets reactors are more efficient than Tee-mixers, in converting the pressure drop into turbulent kinetic energy and as a consequence in producing smaller particles. The very simple modelling approach proposed here (based on the evaluation of the mixing time) seems to be able to correlate well experimental data obtained under different operating conditions, independently on the type of device used. Moreover, in the case of poly-?-caprolactone it was also possible to successfully quantify the particle formation time with a simple power law, further exploiting the model.     

Simple maximum likelihood estimates of efficacy in randomized trials and before-and-after studies, with implications for meta-analysis

Efficacy, which we define as the effect of receiving intervention on health outcomes among a group of subjects, is the quantity of interest for many investigators. In contrast, intent-to-treat analyses in randomized trials and their analogue for observational before-and-after studies compare outcomes between randomization groups or before-and-after time periods. When there is switching of interventions, estimates based on intent-to-treat are biased for estimating efficacy. By constructing a model based on potential outcomes, one can make reasonable assumptions to estimate efficacy under 'all-or-none' switching of interventions in which switching occurs immediately after randomization or at the start of the time period. This paper reviews the basic methodology, with emphasis on simple maximum likelihood estimates that arise with completely observed outcomes, partially missing binary outcomes, and discrete-time survival outcomes. Particular attention is paid to estimating efficacy in meta-analysis, where the interpretation is much more straightforward than with intent-to-treat analyses.     

Random effects and latent processes approaches for analyzing binary longitudinal data with missingness: a comparison of approaches using opiate clinical trial data

The analysis of longitudinal data with non-ignorable missingness remains an active area in biostatistics research. This article discusses various random effects and latent process models which have been proposed for analyzing longitudinal binary data subject to both non-ignorable intermittent missing data and dropout. These models account for non-ignorable missingness by introducing random effects or a latent process which is shared between the response model and the model for the missing-data mechanism. We discuss various random effects and latent processes approaches and compare these approaches with analyses from an opiate clinical trial data set, which had high proportion of intermittent missingness and dropout. We also compare these random effect and latent process approaches with other methods for accounting for non-ignorable missingness using this data set.     

Analytical studies on the temperature distribution in spiral plate heat exchangers: Straightforward design formulae for efficiency and mean temperature difference

The temperature distribution in spiral plate heat exchangers has been calculated numerically to obtain the efficiency and the logarithmic mean temperature difference (LMTD) correction factors F as a function of the number of transfer units N, the number of turns n, and the heat capacity rate ratio C. It has been found that the LMTD correction factors, when plotted against the number of transfer units per turn N/n, fall approximately on a single curve. That curve for balanced countercurrent operation (C = −1) can be very closely represented by the simple formula F = (n/N)tanh(N/n). From that simple analytic representation of our numerical results it was concluded that a simpler physical model might exist to represent the overall behaviour of a spiral plate heat exchanger equally well. In fact, a countercurrent cascade of n cocurrent heat exchangers does result exactly in the above-mentioned formula for the LMTD correction factor. From that model the F-factors for other heat capacity rate ratios C (−1 < C 0) can also be calculated and they are in sufficient agreement with the numerical results.     

Swirling effects on the performance of the micro-particle acceleration and penetration: parametric studies

A unique biomedical delivery system (biolistics), for micro-sized powder formulation of drugs (typically protein- and/or DNA-based macromolecules) to be effectively and efficiently delivered into human skin or mucosal tissue for the treatment of a scope of diseases, has been proposed. One of the key concerns for designing and evaluating the biolistic system is to warrant that micro-particles are accelerated and penetrated in to the skin with a controllable velocity range and uniform spatial distribution for optimal targeting the cells of interest. In this paper, we numerically interrogate the performance of a prototype biolistic device, designed for a uniform micro-particle acceleration and penetration. Swirling effects on the gas-particle dynamics, the particle acceleration and penetration as well as the device performance are presented and interpreted. Variations of the micro-particle velocity range and spatial distribution with swirl ratios are examined. The ability of the micro-particles penetrating in to a model skin target is demonstrated and discussed.     

Morphology and mechanical properties in the binary blends of isotactic polypropylene and novel propylene-co-olefin random copolymers with isotactic propylene sequence 1. Ethylene-propylene copolymers

The additive effects of the novel ethylene-propylene random (EP) copolymers with high isotacticity in propylene sequence on the morphology and mechanical properties of isotactic polypropylene (iPP) were investigated using polarized optical microscopy, transmission electron microscopy, dynamic mechanical analysis and tensile behavior. According to these results, the EP copolymers with a propylene content of more than 84 mol% were miscible with iPP, in which the crystallizable PP sequences in these EP copolymers were incorporated in crystal lattice of iPP and the other portions in the EP chains were excluded to the amorphous phases. Consequently, they act as tie molecules linking between adjacent lamellae, leading to enhancement of yield toughness of iPP. On the other hand, the EP copolymers with a propylene-unit content of less than 77 mol% were incompatible with iPP. The iPP/EP blends showed the phase-separated morphology.     

Enhancing the stability of microsomal cytochrome b5: a rational approach informed by comparative studies with the outer mitochondrial membrane isoform

The outer mitochondrial membrane isoform of mammalian cytochrome b5 (OM b5) is much less prone to lose heme than the microsomal isoform (Mc b5), with a conserved difference at position 71 (leucine versus serine) playing a major role. We replaced Ser71 in Mc b5 with Leu, with the prediction that it would retard heme loss by diminishing polypeptide expansion accompanying rupture of the histidine to iron bonds. The strategy was partially successful in that it slowed dissociation of heme from its less stable orientation in bMc b5 (B). Heme dissociation from orientation A was accelerated to a similar extent, however, apparently owing to increased binding pocket dynamic mobility related to steric strain. A second mutation (L32I) guided by results of previous comparative studies of Mc and OM b5s diminished the steric strain, but much greater relief was achieved by replacing heme with iron deuteroporphyrin IX (FeDPIX). Indeed, the stability of the Mc(S71L) b5 FeDPIX complex is similar to that of the FeDPIX complex of OM b5. The results suggest that maximizing heme binding pocket compactness in the apo state is a useful general strategy for increasing the stability of engineered or designed proteins.     

Efficacy and safety of turmeric and curcumin in lowering blood lipid levels in patients with cardiovascular risk factors: a meta-analysis of randomized controlled trials

Background

Dyslipidemia is an important and common cardiovascular risk factor in the general population. The lipid-lowering effects of turmeric and curcumin are unconfirmed. We performed a meta-analysis to assess the efficacy and safety of turmeric and curcumin in lowering blood lipids in patients at risk of cardiovascular disease (CVD).

Methods

A comprehensive literature search was conducted on PubMed, Embase, Ovid, Medline and Cochrane Library databases to identify randomized controlled trials (published as of November 2016) that assessed the effect of turmeric and curcumin on blood lipid levels including total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG). Pooled standardized mean difference (SMD) with 95% confidence interval (CI) was used to assess the effect.

Results

The analysis included 7 eligible studies (649 patients). Turmeric and curcumin significantly reduced serum LDL-C (SMD = ?0.340, 95% confidence interval [CI]: ?0.530 to ?0.150, P < 0.0001) and TG (SMD = ?0.214, 95% CI: ?0.369 to ?0.059, P = 0.007) levels as compared to those in the control group. These may be effective in lowering serum TC levels in patients with metabolic syndrome (MetS, SMD = ?0.934, 95% CI: ?1.289 to ?0.579, P < 0.0001), and turmeric extract could possibly have a greater effect on reducing serum TC levels (SMD = ?0.584, 95% CI: ?0.980 to ?0.188, P = 0.004); however, the efficacy is yet to be confirmed. Serum HDL-C levels were not obviously improved. Turmeric and curcumin appeared safe, and no serious adverse events were reported in any of the included studies.

Conclusions

Turmeric and curcumin may protect patients at risk of CVD through improving serum lipid levels. Curcumin may be used as a well-tolerated dietary adjunct to conventional drugs. Further research is required to resolve uncertainties related to dosage form, dose and medication frequency of curcumin.

     

Study of the BMIM-PF6: Acetonitrile binary mixture as a solvent for electrochemical studies involving CO2

A series of binary mixtures ranging from 0 vol.% to 100 vol.% CH₃CN in BMIM-PF₆ were investigated to identify an optimum ratio for use in electrochemical studies involving CO₂. Density, viscosity and conductivity were measured for the range of binary mixtures and compared to previously published data. The electrochemistry of a model compound, azobenzene, was studied as well. The data indicated that a binary mixture containing 15–20 vol.% (approximately 0.5 mol fraction) CH₃CN in BMIM-PF₆ was optimal for electrochemistry, and FTIR of CO₂ saturated solutions demonstrated that the solubility of CO₂ in the 15–20% CH₃CN mixtures was only about 10% lower than that seen in the neat BMIM-PF₆.     

A study of the combined effects of kinetic parameters and flow models on conversions for second order reactions

The present paper is a study of the interplay between kinetic parameters and different flow patterns and its effect on fractional conversions for second order reactions with arbitrary stoichiometry and arbitrary ratios between the initial concentrations of the reactants. The models studied are the normal, segregated and maximum-mixed axial dispersion and tanks-in-series models. The calculations required have been performed with the aid of digital simulation and the results are presented in diagrams making possible the determination of the fractional conversion for ten different models. When plotted as a function of a reaction rate group the absolute value of the difference between the conversions for the normal and segregated models always attains its highest value for the limiting model represented by complete backmixing, while this difference is zero for the opposite limiting model, i.e. plug flow. In the case of maximum-mixed and normal models this difference attains its highest value between plug flow and complete backmixing, but the exact value is dependent on other parameter values. The diagrams indicate that it is more important to choose the proper model for certain parameter combinations than for others: the maximum difference between the conversions for different models is about 8%; the lowest is zero.     

Correlations of the first normal stress difference with shear stress and of the storage modulus with loss modulus for homopolymers

The effects of temperature, molecular weight and its distribution, side chain branching, and the structure of polymers on the elastic behavior of bulk homopolymers were investigated, by using logarithmic plots of first normal stress difference (N₁) against shear stress (σ₁₂) and logarithmic plots of storage modulus (G′) against loss modulus (G″). For the investigation, we have used data from the literature as well as our recent experimental results, covering a very wide range of temperature and shear stress or loss modulus. It has been found that such plots are very weakly sensitive to (or virtually independent of) temperature and to the molecular weight of high molecular weight polymers, but strongly dependent upon the molecular weight distribution and the degree of side chain branching. A theoretical interpretation of the observed correlations is presented, using molecular theories.     

Loop flexibility and solvent dynamics as determinants for the selective inhibition of cyclin-dependent kinase 4: comparative molecular dynamics simulation studies of CDK2 and CDK4

The design and discovery of selective cyclin-dependent kinase 4 (CDK4) inhibitors have been actively pursued in order to develop therapeutic cancer treatments. By means of a consecutive computational protocol involving homology modeling, docking experiments, and molecular dynamics simulations, we examine the characteristic structural and dynamic properties that distinguish CDK4 from CDK2 in its complexation with selective inhibitors. The results for all three CDK4-selective inhibitors under investigation show that the large-amplitude motion of a disordered loop of CDK4 is damped out in the presence of the inhibitors whereas their binding in the CDK2 active site has little effect on the loop flexibility. It is also found that the binding preference of CDK4- selective inhibitors for CDK4 over CDK2 stems from the reduced solvent accessibility in the active site of the former due to the formation of a stable hydrogen-bond triad by the Asp99, Arg101, and Thr102 side chains at the top of the active-site gorge. Besides the differences in loop flexibility and solvent accessibility, the dynamic stabilities of the hydrogen bonds between the inhibitors and the side chain of the lysine residue at the bottom of the active site also correlate well with the relative binding affinities of the inhibitors for the two CDKs. These results highlight the usefulness of this computational approach in evaluating the selectivity of a CDK inhibitor, and demonstrate the necessity of considering protein flexibility and solvent effects in designing new selective CDK4-selective inhibitors.     

Isothermal vapor-liquid equilibria for the binary systems of ethylene glycol monopropyl ether with 2,2-dimethylbutane and 2,3-dimethylbutane

Isothermal vapor liquid equilibria for the binary system of ethylene glycol monopropyl ether with 2,2-dimehylbutane and 2,3-dimethylbutane were measured in a circulating water bath at 303.15, 318.15, and 333.15 K. The apparatus was in-house designed and manufactured. Consistency testing of the apparatus was done by comparing the measured vapor pressures to the calculated vapor pressures from the Antoine equation. The measured systems were correlated with a Peng-Robinson equation of state (PR) combined with Wong-Sandler mixing rule for the vapor phase, and NRTL, UNIQUAC, and Wilson activity coefficient models for the liquid phase. All the measured systems showed good agreement with the correlation results.     

Isobaric vapour-liquid equilibrium for the binary mixtures of 1-bromobutane with isomeric butanols at 40.0 and 101.3 kpa

A dynamic recirculating still was employed to measure isobaric vapour-liquid equilibrium at 40.0 and 101.3 kPa for the binary systems 1-bromobutane and each of the isomers of butanol. All mixtures show azeotropes at both pressures. The experimental VLE data are thermodynamically consistent and were correlated using Margules, Van Laar, Wilson, NRTL and UNIQUAC equations.     

Isobaric vapor-liquid equilibrium and liquid-phase enthalpy of mixing data for the binary mixtures of m- or p-Xylene with cyclohexanol

Isobaric vapor-liquid equilibrium data and liquid-phase enthalpy of mixing are investigated for the binary mixtures of m- or p-xylene with cyclohexanol. Allowance for self-association of the cyclic alcohol is made when assessing the thermodynamic consistency of the experimental data. Activity coefficients are correlated to mole fractions through the Wilson Equation, the parameters of which are obtained by the method of maximum likelihood and compared with the ones given by the conventional unweighted least-squares procedure.