Melting Temperature Measurements Research Articles

L-DNA-Based Melt Analysis Enables Within-Sample Validation of PCR Products.

The melt analysis feature in most real-time polymerase chain reaction (PCR) instruments is a simple method for determining if expected or unexpected products are present. High-resolution melt (HRM) analysis seeks to improve the precision of melt temperature measurements for better PCR product sequence characterization. In the area of tuberculosis (TB) drug susceptibility screening, sequencing has shown that a single base change can be sufficient to make a first-line TB drug ineffective. In this study, a reagent-based calibration strategy based on synthetic left-handed (L)-DNA, designated LHRM, was developed to confirm validation of a PCR product with single base resolution. To test this approach, a constant amount of a double-stranded L-DNA melt comparator was added to each sample and used as a within-sample melt standard. The performance of LHRM and standard HRM was used to classify PCR products as drug-susceptible or not drug-susceptible with a test bed of nine synthetic katG variants, each containing single or multiple base mutations that are known to confer resistance to the first-line TB drug isoniazid (INH). LHRM achieved comparable classification to standard HRM relying only on within-sample melt differences between L-DNA and the unknown PCR product. Using a state-of-the-art calibrated instrument and multiple sample classification analysis, standard HRM was performed at 66.7% sensitivity and 98.8% specificity. Single sample analysis incorporating L-DNA for reagent-based calibration into every sample maintained high performance at 77.8% sensitivity and 98.7% specificity. LHRM shows promise as a high-resolution single sample method for validating PCR products in applications where the expected sequence is known.

Influence of TiO2/SiO2 and BaO/CaO ratios on viscosity, crystallization and structure of high-TiO2 mold slags for casting of high-Ti steel

In the current study, the influence of TiO2/SiO2 and BaO/CaO ratios on viscosity, crystallization and structure of high-TiO2 mold slags was discussed through the measurement of viscosity-temperature relationship, melting temperature, crystallization temperature, crystallization rate and phases, and Raman spectrum. With the substitution of SiO2 by TiO2 in slags from 0 % to 12 %, the viscosity at 1300 °C, the melting temperature and break temperature decreased and then increased, while those of slags with the substitution of CaO by BaO from 4 % to 16 % decreased. With the substitution of SiO2 by TiO2 from 0 % to 10 %, crystallization phases gradually changed from cuspidine (Ca4Si2F2O7) to perovskite (CaTiO3), the initial and complete crystallization temperatures had the tendency to increase from 918 °C to 1260 °C and from 857 °C to 1139 °C, respectively, and the overall crystallization ability of slags increased. With the substitution of CaO by BaO from 4 % to 16 %, the initial and complete crystallization temperature of these slags decreased, and the overall crystalline ability decreased. With the substitution of SiO2 by TiO2 from 0 % to 10 %, structural units changed from the simple units to complex units, but the transition was opposite with the substitution from 10 % to 12 %, which was related to the transition of TiO2 from basic oxide to amphoteric oxide. With the substitution of CaO by BaO from 4 % to 16 %, the degree of polymerization and the viscosity of theses slags decreased, which was related to the supplement of more active O2− ion from BaO. Hence, the excessive substitution of SiO2 by TiO2 under the steel-slag reaction would cause the increase of the slag viscosity and crystallization ability, while the substitution of CaO by BaO could weaken the variation of slag viscosity and crystallization ability.

Development of Allosteric Ribozymes for ATP and l-Histidine Based on the R3C Ligase Ribozyme.

During the evolution of the RNA, short RNAs are thought to have joined together to form long RNAs, enhancing their function as ribozymes. Previously, the artificial R3C ligase ribozyme (73 nucleotides) was successfully reduced to 46 nucleotides; however, its activity decreased significantly. Therefore, we aimed to develop allosteric ribozymes, whose activities could be regulated by effector compounds, based on the reduced R3C ligase ribozyme (R3C-A). Among the variants prepared by fusing an ATP-binding aptamer RNA with R3C-A, one mutant showed increased ligation activity in an ATP-dependent manner. Melting temperature measurements of the two RNA mutants suggested that the region around the aptamer site was stabilized by the addition of ATP. This resulted in a suitable conformation for the reaction at the ligation site. Another ribozyme was prepared by fusing R3C-A with a l-histidine-binding aptamer RNA, and the ligase activity increased with increasing l-histidine concentrations. Both ATP and l-histidine play prominent roles in current molecular biology and the interaction of RNAs and these molecules could be a key step in the evolution of the world of RNAs. Our results suggest promise in the development of general allosteric ribozymes that are independent of the type of effector molecule and provide important clues to the evolution of the RNA world.

Machine-Learned Potential Energy Surfaces for Free Sodium Clusters with Density Functional Accuracy: Applications to Melting

Gaussian Process Regression based Gaussian Approximation Potential has been used to develop machine learned interatomic potentials having density functional accuracy, for free sodium clusters. The training data was generated from a large sample of over 100,000 data points computed for clusters in the size range of N = 40–200, where N denotes the number of atoms in the cluster, using the density functional method as implemented in the VASP code. Two models have been developed, model M1 using data for N = 55 only, and model M2 using additional data from larger clusters. The models are intended for computing thermodynamic properties using molecular dynamics. Hence, particular attention has been paid to improve the fitting of the forces. Although it was possible to obtain a good fit using the data of Na55 only, additional data points from larger clusters were needed to get better accuracies in energies and forces for larger sizes. Surprisingly, the model M1 could be significantly improved by adding about 50 data points per cluster from the larger sizes. Thus, it turns out that the best fit can be obtained by carefully selecting a small number of data points viz. 1,900 and 1,300 configurations for the two models M1 and M2, respectively. These two models have been deployed to compute the heat capacities of Na55. The heat capacities of Na147 and about 40 isomers for larger clusters of sizes N = 147, 200, 201, and 252, have been obtained using the final model M2. There is an excellent agreement between the computed and experimentally measured melting temperatures. The geometries of these isomers have been further optimized by density functional theory. The mean absolute error with respect to DFT energies is found to be about 7 meV/atom or less. The errors in the lowest interatomic bond lengths are below 2% in almost all the cases.

A high-throughput differential scanning fluorimetry method for rapid detection of thermal stability and iron saturation in lactoferrin

Thermal stability and iron saturation of lactoferrin (LF) are of great significance not only for the evaluation of the biological activities of LF but also for the optimization of the isolation and drying process parameters. Differential scanning calorimetry (DSC) is a well-established and efficient method for thermal stability and iron saturation detection in LF. However, multiple DSC measurements are typically performed sequentially, thus time-consuming and low throughput. Herein, we introduced the differential scanning fluorimetry (DSF) approach to overcome such limitations. The DSF can monitor LF thermal unfolding with a commonly available real-time PCR instrument and a fluorescent dye (SYPRO orange or Glomelt), and the measured melting temperature of LF is consistent with that determined by DSC. On the basis of that, a new quantification method was established for determination of iron saturation levels using the linear correlation of the degree of ion saturation of LF with DSF measurements. Such DSF method is simple, inexpensive, rapid (<15 min), and high throughput (>96 samples per experiment), and provides a valuable alternative tool for thermal stability detection of LF and other whey proteins.

Evaporation and its Effects on Physico-Chemical Properties of PbO-containing Slag

PbO as well as other volatiles will evaporate at high temperature. In the measure of relevant slag property, the slag will be kept at high temperature for a long time (even several hours). The continuous evaporation will result in uncertainty of the measured results. In another point of view, that means the measured result is no longer in consistent with the pre-determined slag composition, but a new one changed obviously. For high or medium PbO content slag, the weight loss can reach to 20∼40 % at high temperature. The effect is not negligible. In this work, the evaporation and physicochemical property (melting point and viscosity) measurement of typical PbO-containing slag were jointly analyzed based on calculation, TG-DSC, melting temperature and viscosity measurement. A deviation method based on traditional measurement ways was suggested and practiced. It is proved that to take physicochemical property value with traditional method and the get the in-time composition to match the measured values is feasible. how obtain in-time composition is also discussed and tried. The work will be of extensive reference significance to other slag system with higher volatiles.

Numerical modelling of heating and melting of metal in a mini industrial direct current electrical arc furnace

Purpose The purpose of this paper is the study of the electro-vortex flow (EVF) as well as heating and melting processes for mini industrial direct current electric arc furnace (DC EAF). Design/methodology/approach A mini DC EAF was designed, manufactured and installed to study the industrial processes of heating and melting a small amount of melt, being 4.6 kg of steel in the case under study. Numerical modelling of metal melting was performed using the enthalpy and porosity approach at equal values and non-equal values of the solidus and liquidus temperatures of the metal. The EVF of the liquid phase of metal was computed using the large eddy simulation model of turbulence. Melt temperature measurements were made using an infrared camera and a probe with a thermocouple sensor. The melt speed was estimated by observing the movement of particles at the top surface of melt. Findings The thermal flux for metal heating and melting, which is supplied through an arc spot at the top surface of metal, is estimated using the thermal balance of the furnace at melting point. The melting time was estimated using numerical modelling of heating and melting of metal. The process started at room temperature and finished once whole volume of metal was molten. The evolution of the solid/melt phase boundary as well as evolution of EVF patterns of the melt was studied. Originality/value Numerical studies of heating and melting processes in metal were performed in the case of intensive liquid phase turbulent circulation due to the Lorentz force in the melt, which results from the interaction of electrical current with a self-magnetic field.

Design of stable circular permutants of the GroEL chaperone apical domain

Enhancing protein stability holds paramount significance in biotechnology, therapeutics, and the food industry. Circular permutations offer a distinctive avenue for manipulating protein stability while keeping intra-protein interactions intact. Amidst the creation of circular permutants, determining the optimal placement of the new N- and C-termini stands as a pivotal, albeit largely unexplored, endeavor. In this study, we employed PONDR-FIT’s predictions of disorder propensity to guide the design of circular permutants for the GroEL apical domain (residues 191–345). Our underlying hypothesis posited that a higher predicted disorder value would correspond to reduced stability in the circular permutants, owing to the increased likelihood of fluctuations in the novel N- and C-termini. To substantiate this hypothesis, we engineered six circular permutants, positioning glycines within the loops as locations for the new N- and C-termini. We demonstrated the validity of our hypothesis along the set of the designed circular permutants, as supported by measurements of melting temperatures by circular dichroism and differential scanning microcalorimetry. Consequently, we propose a novel computational methodology that rationalizes the design of circular permutants with projected stability.8ghBPrif1HpKfHNvAL1G2xVideo

Synthesis and study of Arginin-containing iron and cobalt chelates

Synthesis conditions have been established and arginin-containing iron and cobalt chelate compounds with general formula: Me(Arg)n(CH3COO)2·mH2O, where Me = Fe, Co; Arg – neutral arginin molecule, n = 1÷3; m = 1÷4 have been synthesized. Synthesized chelates have been studied using a number of physical and chemical methods. In particular, the content has been established via trace element analysis, while individuality has been identified using melting temperature measurement and diffractographic method. According to study of qualitative solubility chelates are well soluble in water, though they are poorly soluble in organic solvents. Using the conductometric method there has been calculated the dissociation constant of chelate compound containing solutions. On the basis of preliminary trial tests conducted with a purpose of biological activity study, there has been expressed an opinion that entry of arginin-containing iron and cobalt chelates into composition of broilers’ combined feed premixes has had a positive impact on poultry live weight gain and poultry survival rate. An opinion on the reasonability of basic tests conduction has been given in order to determine the doses of arginin-containing iron and cobalt chelate compounds optimal for broilers.

Verification Method for Determination of Melting Temperature and Enthalpy Changes (∆H) Using Differential Scanning Calorimeter

Verification of measurement method for determination of melting temperature and enthalpy changes using Differential Scanning Calorimeter has been carried out. This study was done to ensure that the method used can be applied in the laboratory with valid results and uncertainty. The verification method in this research consists of accuracy and precision. Accuracy was done by comparing measurement results with reference values using the t-student test. Precision can be seen in its repeatability and reproducibility. In this study, method verification of melting temperature measurement was carried out by thermal analysis using Differential Scanning Calorimeter (DSC) based on ISO 11357-3: 2018 method concerning determining temperature and enthalpy changes in melting and crystallization. The results showed that the method used to determine melting temperature and enthalpy changes (∆H) had met the repeatability and reproducibility requirements. The RSD (Relative Standard Deviation) value was less than 2%, and the accuracy met the acceptance requirements with a t-count smaller than the t-table in a 95% confidence level. It means that the results are not significantly different from reference values, so the method can be used in the laboratory. Keyword: verification method, melting temperature, differential scanning calorimetry

Experimental study on the sintering characteristics of biomass ash

The alkaline metal content in biomass is high, which leads to a low initial sintering temperature. Therefore, during the process of direct biomass combustion for power generation, there are serious problems such as ash deposition and slagging on the heating surface, which has become a technical bottleneck for the safe, stable and long-term operation of boilers. In industry, the melting characteristics of ash are commonly used to guide boiler design and operation. However, traditional measurement of ash melting temperature has a large subjective error, and the releasing of alkaline metals during the measurement process results bit higher value, which affects the accuracy of the measured characteristic temperature. Comparingly, the initial sintering temperature is lower than the deformation temperature of the ash. This article provides a device for measuring the sintering temperature of biomass ash by using the pressure drop method. A novel two ash chamber system was invented, in which the alkali element released from the first ash chamber was captured by the downstream second ash chamber to compensate the escaping of alkali element. The initial sintering temperature of the second ash chamber has more accuracy with lower value than that measured by the traditional single sample chamber. XRD was used to analyze the mineral composition and causes of sintering of the ash samples before and after sintering. The results show that the sintering mechanisms of different types of biomass are different. In addition, combined with SEM analysis of rice husk, fruit core, rapeseed straw, and corn straw, the results show that the initial sintering temperature of the ash samples measured by the double chamber measurement method is more accurate than that measured by the single chamber measurement method, further validating the reliability of the two ash column system.

The 2.4 Å structure of Zymomonas mobilis pyruvate kinase: Implications for stability and regulation

Human liver pyruvate kinase (hlPYK) catalyzes the final step in glycolysis, the formation of pyruvate (PYR) and ATP from phosphoenolpyruvate (PEP) and ADP. Fructose 1,6-bisphosphate (FBP), a pathway intermediate of glycolysis, serves as an allosteric activator of hlPYK. Zymomonas mobilis pyruvate kinase (ZmPYK) performs the final step of the Entner-Doudoroff pathway, which is similar to glycolysis in that energy is harvested from glucose and pyruvate is generated. The Entner-Doudoroff pathway does not have FBP as a pathway intermediate, and ZmPYK is not allosterically activated. In this work, we solved the 2.4 Å X-ray crystallographic structure of ZmPYK. The protein is dimeric in solution as determined by gel filtration chromatography, but crystallizes as a tetramer. The buried surface area of the ZmPYK tetramerization interface is significantly smaller than that of hlPYK, and yet tetramerization using the standard interfaces from higher organisms provides an accessible low energy crystallization pathway. Interestingly, the ZmPYK structure showed a phosphate ion in the analogous location to the 6-phosphate binding site of FBP in hlPYK. Circular Dichroism (CD) was used to measure melting temperatures of hlPYK and ZmPYK in the absence and presence of substrates and effectors. The only significant difference was an additional phase of small amplitude for the ZmPYK melting curves. We conclude that the phosphate ion plays neither a structural or allosteric role in ZmPYK under the conditions tested. We hypothesize that ZmPYK does not have sufficient protein stability for activity to be tuned by allosteric effectors as described for rheostat positions in the allosteric homologues.

Odd–even disparity in the population of slipped hairpins in RNA repeat sequences with implications for phase separation

Low-complexity nucleotide repeat sequences, which are implicated in several neurological disorders, undergo liquid-liquid phase separation (LLPS) provided the number of repeat units, n, exceeds a critical value. Here, we establish a link between the folding landscapes of the monomers of trinucleotide repeats and their propensity to self-associate. Simulations using a coarse-grained Self-Organized Polymer (SOP) model for (CAG)n repeats in monovalent salt solutions reproduce experimentally measured melting temperatures, which are available only for small n. By extending the simulations to large n, we show that the free-energy gap, ΔGS, between the ground state (GS) and slipped hairpin (SH) states is a predictor of aggregation propensity. The GS for even n is a perfect hairpin (PH), whereas it is a SH when n is odd. The value of ΔGS (zero for odd n) is larger for even n than for odd n. As a result, the rate of dimer formation is slower in (CAG)30 relative to (CAG)31, thus linking ΔGS to RNA-RNA association. The yield of the dimer decreases dramatically, compared to the wild type, in mutant sequences in which the population of the SH decreases substantially. Association between RNA chains is preceded by a transition to the SH even if the GS is a PH. The finding that the excitation spectrum-which depends on the exact sequence, n, and ionic conditions-is a predictor of self-association should also hold for other RNAs (mRNA for example) that undergo LLPS.

Analysis of Ash Melting Temperatures of Agricultural Pellets Detected during Different Conditions

Agricultural and other residues are promising renewable energy sources. However, they can cause problems in combustion processes. One of these problems is also low ash melting temperatures. Except, the ash melting behavior can be impacted by many factors, such as ash preparation or used atmosphere. This article deals with comparing different atmosphere conditions during measurements of ash melting temperatures of three agricultural pellets: alfalfa, straw, and hay. The first one was oxidizing with compressed air and nitrogen. The second atmosphere was reduced with the air purge, and the last was only reduced, consisting of 60% carbon monoxide and 40% carbon dioxide. Differences between individual atmospheres were none, up to 9.8%. The most significant differences have appeared between oxidizing and reducing atmospheres. In general, the oxidizing atmosphere presents a less expensive way. More attention should be paid to the use of oxidizing atmosphere for applications in heat sources mainly due to its similarity to the combustion process. However, it would be suitable to realize more comprehensive research regarding ash preparation in different ways and with using of different types of fuel.

Superstructure-dependent stability of DNA origami nanostructures in the presence of chaotropic denaturants.

The structural stability of DNA origami nanostructures in various chemical environments is an important factor in numerous applications, ranging from biomedicine and biophysics to analytical chemistry and materials synthesis. In this work, the stability of six different 2D and 3D DNA origami nanostructures is assessed in the presence of three different chaotropic salts, i.e., guanidinium sulfate (Gdm2SO4), guanidinium chloride (GdmCl), and tetrapropylammonium chloride (TPACl), which are widely employed denaturants. Using atomic force microscopy (AFM) to quantify nanostructural integrity, Gdm2SO4 is found to be the weakest and TPACl the strongest DNA origami denaturant, respectively. Despite different mechanisms of actions of the selected salts, DNA origami stability in each environment is observed to depend on DNA origami superstructure. This is especially pronounced for 3D DNA origami nanostructures, where mechanically more flexible designs show higher stability in both GdmCl and TPACl than more rigid ones. This is particularly remarkable as this general dependence has previously been observed under Mg2+-free conditions and may provide the possibility to optimize DNA origami design toward maximum stability in diverse chemical environments. Finally, it is demonstrated that melting temperature measurements may overestimate the stability of certain DNA origami nanostructures in certain chemical environments, so that such investigations should always be complemented by microscopic assessments of nanostructure integrity.

Melt Temperature Estimation by Machine Learning Model Based on Energy Flow in Injection Molding.

Highly reliable and accurate melt temperature measurements in the barrel are necessary for stable injection molding. Conventional sheath-type thermocouples are insufficiently responsive for measuring melt temperatures during molding. Herein, machine learning models were built to predict the melt temperature after plasticizing. To supply reliably labeled melt temperatures to the models, an optimized temperature sensor was developed. Based on measured high-quality temperature data, three machine learning models were built. The first model accepted process setting parameters as inputs and was built for comparisons with previous models. The second model accepted additional measured process parameters related to material energy flow during plasticizing. Finally, the third model included the specific heat and part weights reflecting the material energy, in addition to the features of the second model. Thus, the third model outperformed the others, and its loss decreased by more than 70%. Meanwhile, the coefficient of determination increased by about 0.5 more than those of the first model. To reduce the dataset size for new materials, a transfer learning model was built using the third model, which showed a high prediction performance and reliability with a smaller dataset. Additionally, the reliability of the input features to the machine learning models were evaluated by shapley additive explanations (SHAP) analysis.

In-line Process and Material Property Measurement in Injection Moulding - a Theoretical Review

ABSTRACT In running production the measurement of process and material properties in-line, is a requirement to design and implement effective process control in injection moulding. This work presents a structured thorough analysis and review of the research concerned with in-line measurements of selected processes and material properties on the injection moulding machines. This review sets the current state of art within a range of process and material properties, and identifies areas for future research. The process and material property measurements reviewed are; Viscosity, Melt temperature, pvT and Melt density. It is identified that the largest research effort has been placed on the measurement of viscosity and melt temperature, whereas pvT and melt density measurement are less developed. Finally, gaps within the literature are identified and the proposal of a direction within the field is stated.

On‐line melt temperature measurements for polymer injection molding through an instrumented annular duct

AbstractPolymer processing requires reliable monitoring equipment to ensure product quality, improve energy efficiency and apply advanced control strategies. This work tests an instrumented annular duct as a nozzle on the downstream side of the screw‐barrel to analyze the thermal behavior of the polymer flow in an injection molding machine. The plasticization step is first studied, and then virtual injection molding cycles are performed. The measurements via the instrumented annular duct show that the melt temperature decreases during fast production, due to the lack of residence time in the barrel for the material to be sufficiently heated by conduction. The instrumented annular duct also enables detection of changes in melt temperature over time during a single injection. Moreover, the experiments prove the robustness of the temperature measurements in an annular geometry for process monitoring.

Large-scale application of free energy perturbation calculations for antibody design

Alchemical free energy perturbation (FEP) is a rigorous and powerful technique to calculate the free energy difference between distinct chemical systems. Here we report our implementation of automated large-scale FEP calculations, using the Amber software package, to facilitate antibody design and evaluation. In combination with Hamiltonian replica exchange, our FEP simulations aim to predict the effect of mutations on both the binding affinity and the structural stability. Importantly, we incorporate multiple strategies to faithfully estimate the statistical uncertainties in the FEP results. As a case study, we apply our protocols to systematically evaluate variants of the m396 antibody for their conformational stability and their binding affinity to the spike proteins of SARS-CoV-1 and SARS-CoV-2. By properly adjusting relevant parameters, the particle collapse problems in the FEP simulations are avoided. Furthermore, large statistical errors in a small fraction of the FEP calculations are effectively reduced by extending the sampling, such that acceptable statistical uncertainties are achieved for the vast majority of the cases with a modest total computational cost. Finally, our predicted conformational stability for the m396 variants is qualitatively consistent with the experimentally measured melting temperatures. Our work thus demonstrates the applicability of FEP in computational antibody design.

Metal Ion Binding in Wild-Type and Mutated Frataxin: A Stability Study.

This work studies the stability of wild-type frataxin and some of its variants found in cancer tissues upon Co2+ binding. Although the physiologically involved metal ion in the frataxin enzymatic activity is Fe2+, as it is customarily done, Co2+ is most often used in experiments because Fe2+ is extremely unstable owing to the fast oxidation reaction Fe2+ → Fe3+. Protein stability is monitored following the conformational changes induced by Co2+ binding as measured by circular dichroism, fluorescence spectroscopy, and melting temperature measurements. The stability ranking among the wild-type frataxin and its variants obtained in this way is confirmed by a detailed comparative analysis of the XAS spectra of the metal-protein complex at the Co K-edge. In particular, a fit to the EXAFS region of the spectrum allows positively identifying the frataxin acidic ridge as the most likely location of the metal-binding sites. Furthermore, we can explain the surprising feature emerging from a detailed analysis of the XANES region of the spectrum, showing that the longer 81-210 frataxin fragment has a smaller propensity for Co2+ binding than the shorter 90-210 one. This fact is explained by the peculiar role of the N-terminal disordered tail in modulating the protein ability to interact with the metal.