With the help of the one-dimensional random Potts-like model, we study the origins of fine structures observed on differential melting profiles of double-stranded DNA. We theoretically assess the effects of sequence arrangement on DNA melting curves through the comparison of results for random, correlated, and block sequences. Our results re-confirm the smearing out of the fine structure with the increase in chain length for all types of sequence arrangements and suggest that the fine structure is a finite-size effect. We have found that the fine structures on melting curves of chains comprised of blocks with correlations in sequence are more persistent, probably because of increased sequence disorder the blocks introduce. Many natural DNAs show a well-expressed fine structure of melting profiles. Our results for block sequences may suggest the existence of such sequence motifs in natural DNA sequences.

High-resolution melt (HRM) analysis is a closed-tube technique for detecting single nucleotide polymorphisms (SNPs). However, it has limited use in high-resolution melting devices, even those with high thermal accuracy (HTA). In addition to the cost of switching to these specialized devices, the presence of nearest neighbour neutral changes (class III, IV SNPs and small indels) made HRM-based assays a challenging task due to reduced sensitivity. This study aimed to design a common modified competitive amplification of differently melting amplicons (CADMA)-based assay to address these challenges by generating allele-specific qPCR products that are detectable on most qPCR platforms. For this study, SNPs were selected from all four classes of SNPs (class I: C/T or G/A mutation; class II: C/A or G/T mutation; class III: G/C mutation; class IV: A/T mutation). A single base pair and 19 bp indels were also chosen to simulate how CADMA primers could be designed for indels of varying lengths. The melting temperatures (Tm) were determined using IDT oligoAnalyzer. qPCR and melt data acquisition were performed on the CFX96 qPCR platform, and the melt curve data were analyzed using Precision Melt software (Bio-Rad, USA). The clusters for different genotypes were successfully identified with the aid of the control samples, and Tm predictions were carried out using the uMelt batch and Tm online tools for comparison. Using HRM-qPCR assays based on the modified CADMA method, genotyping of various SNPs was successfully carried out. For some SNPs, similarly shaped melt curves were observed for homozygotes and heterozygotes, making shape-based genotype prediction difficult. The Tm values calculated via the Blake and Delcourts (1998) method were the closest to the experimental Tm values after adjusting for the salt concentration. Since HRM assays usually depend on the ΔTm caused by mutations, they are prone to a high error rate due to nearest neighbour neutral changes. The technique developed in this study significantly reduces the failure rates in HRM-based genotyping and could be applied to any SNP or indel in any platform. It is crucial to have a deep understanding of the melt instrument, its accuracy and the nature of the target (SNP class or indel length and GC content of the flanking region). Furthermore, the availability of controls is essential for a high success rate.

Anhydrous milk fat (AMF) and its fractions are used as ingredients in a wide range of food applications. Obtaining the appropriate solid fat content (SFC) is essential to achieve the desired product texture. At present, in-line monitoring techniques to control milk fat crystallization and melting are largely unavailable. The thermal behaviour of milk fat (AMF and four of its fractions) was monitored in a temperature-controlled vessel using an in-line Raman analyser and compared with thermograms generated using differential scanning calorimetry (DSC). The major stages of milk fat crystallization and melting were identified using the in-line Raman analyser. Thermal data from DSC showed excellent linear correlations with Raman spectral data (R2 value of 0.97 for the onset of milk fat crystallisation). Partial least squares regression (PLSR) models were developed using Raman spectra to predict SFC with coefficient of determination (R2Cs) from 0.929 to 0.992 and root mean standard error of calibration (RMSECs) ranging from 3.20 to 10.36%. Results demonstrated Raman spectroscopy has significant potential as a way of monitoring milk fat crystallization and melting processes.

Two anhydrous polymorphs of the novel antiviral medicine nirmatrelvir were discovered during the development of Paxlovid, Pfizer\'s oral Covid-19 treatment. A comprehensive experimental and computational approach was necessary to distinguish the two closely related polymorphs, herein identified as Forms 1 and 4. This approach paired experimental methods, including powder X-ray diffraction and single-crystal X-ray diffraction, solid-state experimental methods, thermal analysis, solid-state nuclear magnetic resonance and Raman spectroscopy with computational investigations comprising crystal structure prediction, Gibbs free energy calculations, and molecular dynamics simulations of the polymorphic transition. Forms 1 and 4 were ultimately determined to be enantiotropically related polymorphs with Form 1 being the stable form above the transition temperature of ∼17 °C and designated as the nominated form for drug development. The work described in this paper shows the importance of using highly specialized orthogonal approaches to elucidate the subtle differences in structure and properties of similar solid-state forms. This synergistic approach allowed for unprecedented speed in bringing Paxlovid to patients in record time amidst the pandemic.

High-density lipoproteins (HDL) are micelle-like particles consisting of a core of triglycerides and cholesteryl esters surrounded by a shell of phospholipid, cholesterol, and apolipoproteins. HDL is considered \"good\" cholesterol, and its concentration in plasma is used clinically in assessing cardiovascular health. However, these particles vary in structure, composition, and therefore function, and thus can be resolved into subpopulations, some of which have specific cardioprotective properties. Mass measurements of HDL by charge detection mass spectrometry (CD-MS) previously revealed seven distinct subpopulations which could be delineated by mass and charge [Lutomski, C. A. et al. Anal. Chem. 2018]. Here, we investigate the thermal stabilities of these subpopulations; upon heating, the particles within each subpopulation undergo structural rearrangements with distinct transition temperatures. In addition, we find evidence for many new families of structures within each subpopulation; at least 15 subspecies of HDL are resolved. These subspecies vary in size, charge, and thermal stability. While this suggests that these new subspecies have unique molecular compositions, we cannot rule out the possibility that we have found evidence for new structural forms within the known subpopulations. The ability to resolve new subspecies of HDL particles may be important in understanding and delineating the role of unique particles in cardiovascular health and disease.

We investigate the melting transition of non-supercoiled circular DNA of different lengths, employing Brownian dynamics simulations. In the absence of supercoiling, we find that melting of circular DNA is driven by a large bubble, which agrees with the previous predictions of circular DNA melting in the presence of supercoiling. By analyzing sector-wise changes in average base-pair distance, our study reveals that the melting behavior of circular DNA closely resembles that of linear DNA. Additionally, we find a marked difference in the thermal stability of circular DNA over linear DNA at very short length scales, an effect that diminishes as the length of circular DNA increases. The stability of smaller circular DNA is linked to the occurrence of transient small bubbles, characterized by a lower probability of growth.

The influence of different preparation methods on the physicochemical properties of amorphous solid forms have gained considerable attention, especially with recent publications on pharmaceutical polyamorphism. In the present study, we have investigated the possible occurrence of polyamorphism in the drug celecoxib (CEL) by investigating the thermal behavior, morphology, structure, molecular mobility and physical stability of amorphous CEL obtained by quench-cooling (QC), ball milling (BM) and spray drying (SD). Similar glass transition temperatures but different recrystallization behaviors were observed for CEL-QC, CEL-BM and CEL-SD using modulated differential scanning calorimetry analysis. A correlation between the different recrystallization behaviors of the three CEL amorphous forms and the respective distinct powder morphologies, was also found. Molecular dynamics simulations however, reveal that CEL presents similar molecular conformational distributions when subjected to QC and SD. Moreover, the obtained molecular conformational distributions of CEL are different from the ones found in its crystal structure and also from the ones found in the lowest-energy structure obtained by quantum mechanical calculations. The type and strength of CEL hydrogen bond interactions found in CEL-QC and CEL-SD systems are almost identical, though different from the ones presented in the crystal structure. Pair distribution function analyses and isothermal microcalorimetry show similar local structures and structural relaxation times, respectively, for CEL-QC, CEL-BM and CEL-SD. The present work shows that not only similar physicochemical properties (glass transition temperature, and structural relaxation time), but also similar molecular conformational distributions were observed for all prepared CEL amorphous systems. Hence, despite their different recrystallization behaviors, the three amorphous forms of CEL did not show any signs of polyamorphism.

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.

As water miscible organic co-solvents are often required for enzyme reactions to improve e.g., the solubility of the substrate in the aqueous medium, an enzyme is required which displays high stability in the presence of this co-solvent. Consequently, it is of utmost importance to identify the most suitable enzyme or the appropriate reaction conditions. Until now, the melting temperature is used in general as a measure for stability of enzymes. The experiments here show, that the melting temperature does not correlate to the activity observed in the presence of the solvent. As an alternative parameter, the concentration of the co-solvent at the point of 50% protein unfolding at a specific temperature T in short c U 50 T is introduced. Analyzing a set of ene reductases, c U 50 T is shown to indicate the concentration of the co-solvent where also the activity of the enzyme drops fastest. Comparing possible rankings of enzymes according to melting temperature and c U 50 T reveals a clearly diverging outcome also depending on the specific solvent used. Additionally, plots of c U 50 versus temperature enable a fast identification of possible reaction windows to deduce tolerated solvent concentrations and temperature.

Silver iodide is a prototype compound of superionic conductors that allows ions to flow through its structure. It exhibits a first-order phase transition at 420 K, characterized by an abrupt change in its ionic conductivity behavior, and above this temperature, its ionic conductivity increases by more than three orders of magnitude. Introducing small concentrations of carbon into the silver iodide structure produces a new material with a mixed conductivity (ionic and electronic) that increases with increasing temperature. In this work, we report the experimental results of the ionic conductivity as a function of the reciprocal temperature for the (AgI)x - C(1-x) mixture at low carbon concentrations (x = 0.99, 0.98, and 0.97). The ionic conductivity behavior as a function of reciprocal temperature was well fitted using a phenomenological model based on a random variable theory with a probability distribution function for the carriers. The experimental data show a proximity effect between the C and AgI phases. As a consequence of this proximity behavior, carbon concentration or temperature can control the conductivity of the (AgI)x - C(1-x) mixture.