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Nucleic acid duplexes are typically analyzed in non-denaturing conditions. Melting temperature (Tm) is the property used to measure duplex stability; however, it is not known how the chromatographic conditions and mobile phase composition affect the duplex stability. We employed differential scanning calorimetry (DSC) method to measure the melting temperature of chemically modified silencing RNA duplex (21 base pairs, 0.15 mM duplex concentration) in mobile phases commonly used in reversed-phase, ion-pair reversed-phase, size exclusion and hydrophilic interaction chromatography. We investigated mobile phases consisting of ammonium acetate, alkylammonium ion-pairing reagents, alkali-ion chlorides, magnesium chloride, and additives including methanol, ethanol, acetonitrile and hexafluoroisopropanol. Increasing buffer concentration enhanced the duplex stability (Tm was 67.1 - 78.2 °C for 10-100 mM [Na+] concentration). The melting temperature decreases with the increase in cation size (70.2 °C in 10 mM [Li+], 68.1 °C in 10 mM [NH4+], 65.6 °C in 10 mM [Cs+], and 56.6 °C in 10 mM [triethylammonium+] solutions). Inclusion of 20 % of organic solvent in buffer reduced the melting temperature by 1-3 °C, and denaturation power increases in the order MeOH

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Hydrogels have the ability to retain large amounts of water within their three-dimensional polymer matrices. These attractive materials are used in medicine and the food industry; they can serve as the basis for structured food products, additives, and various ingredients. Gelatin is one of widely used biopolymers to create hydrogels that exhibit biocompatibility and tunable rheological properties. In this study, we offer a comparative analysis of rheological properties of gelatin-based hydrogels (C = 6.67%), including mammalian gelatins from bovine and porcine skins and fish gelatins from commercial samples and samples extracted from Atlantic cod skin. Mammalian gelatins provide high strength and elasticity to hydrogels. Their melting point lies in the range from 22 to 34 °C. Fish gelatin from cod skin also provides a high strength to hydrogels. Commercial fish gelatin forms weak gels exhibiting low viscoelastic properties and strength, as well as low thermal stability with a melting point of 7 °C. Gelatins were characterized basing on the analysis of amino acid composition, molecular weight distribution, and biopolymer secondary structure in gels. Our research provides a unique rheological comparison of mammalian and fish gelatin hydrogels as a tool for the re-evaluation of fish skin gelatin produced through circular processes.

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An increasing number of antisense oligonucleotides (ASOs) have been approved for clinical use. However, improvements of both efficacy and safety in the central nervous system (CNS) are crucial for the treatment with CNS diseases. We aimed to overcome the crucial issues by our development of various gapmer ASOs with a novel nucleoside derivative including a 2',4'-BNA/LNA with 9-(aminoethoxy)phenoxazine (BNAP-AEO). The various gapmer ASOs with BNAP-AEO were evaluated for thermal stability, in vitro and in vivo efficacy, and acute CNS toxicity. Thermal stability analysis of the duplexes with their complementary RNAs showed that ASOs with BNAP-AEO had a higher binding affinity than those without BNAP-AEO. In vitro assays, when transfected into neuroblastoma cell lines, demonstrated that ASOs with BNAP-AEO, had a more efficient gene silencing effect than those without BNAP-AEO. In vivo assays, involving intracerebroventricular injections into mice, revealed ASOs with BNAP-AEO potently suppressed gene expression in the brain. Surprisingly, the acute CNS toxicity in mice, as assessed through open field tests and scoring systems, was significantly lower for ASOs with BNAP-AEO than for those without BNAP-AEO. This study underscores the efficient gene-silencing effect and low acute CNS toxicity of ASOs incorporating BNAP-AEO, indicating the potential for future therapeutic applications.

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The influence of decreasing the entanglement density of macromolecules on the crystallization of the ß-form of polypropylene was investigated. Polypropylene with seven times less entanglement was obtained from a solution in xylene, and its properties were compared with those of fully entangled polypropylene. To obtain a high ß-phase content, the polymer was nucleated using calcium pimelate. In non-isothermal crystallization studies, accelerated growth of ß-crystals was found, increasing the crystallization temperature. Also, the isothermal crystallization was fastest in the nucleated, partially disentangled polypropylene. Increased growth rate of spherulites and enhanced nucleation activity in the presence of more mobile macromolecules were responsible for the high rate of melt conversion to crystals in the disentangled polypropylene. It was also observed that the equilibrium melting temperature of ß-crystals is lower after disentangling macromolecules. Better conditions for crystal building after reduction of entanglements resulted in enhanced crystallization according to regime II.

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Methicillin-resistant Staphylococcus aureus (MRSA) infection has rapidly spread through various routes. A genomic analysis of clinical MRSA samples revealed an unknown protein, Sav2152, predicted to be a haloacid dehalogenase (HAD)-like hydrolase, making it a potential candidate for a novel drug target. In this study, we determined the crystal structure of Sav2152, which consists of a C2-type cap domain and a core domain. The core domain contains four motifs involved in phosphatase activity that depend on the presence of Mg2+ ions. Specifically, residues D10, D12, and D233, which closely correspond to key residues in structurally homolog proteins, are responsible for binding to the metal ion and are known to play critical roles in phosphatase activity. Our findings indicate that the Mg2+ ion known to stabilize local regions surrounding it, however, paradoxically, destabilizes the local region. Through mutant screening, we identified D10 and D12 as crucial residues for metal binding and maintaining structural stability via various uncharacterized intra-protein interactions, respectively. Substituting D10 with Ala effectively prevents the interaction with Mg2+ ions. The mutation of D12 disrupts important structural associations mediated by D12, leading to a decrease in the stability of Sav2152 and an enhancement in binding affinity to Mg2+ ions. Additionally, our study revealed that D237 can replace D12 and retain phosphatase activity. In summary, our work uncovers the novel role of metal ions in HAD-like phosphatase activity.

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The thermal stability of DNA immobilized on a solid surface is one of the factors that affects the efficiency of solid-phase amplification (SP-PCR). Although variable temperature amplification ensures high specificity of the reaction by precisely controlling temperature changes, excessively high temperatures during denaturation can negatively affect DNA stability. Formamide (FA) enables DNA denaturation at lower temperatures, showing potential for SP-PCR. Research on FA's impacts on DNA microarrays is still limited, necessitating further optimization in exploring the characteristics of FA in SP-PCR according to particular application needs. We immobilized DNA on a chip using a crosslinker and generated DNA microarrays through bridge amplification based on FA denaturation on our automated reaction device. We optimized the denaturation and hybridization parameters of FA, achieving a maximum cluster density of 2.83 × 104 colonies/mm2. Compared to high-temperature denaturation, FA denaturation required a lower template concentration and milder reaction conditions and produced higher cluster density, demonstrating that FA effectively improves hybridization rates on surfaces. Regarding the immobilized DNA stability, the FA group exhibited a 45% loss of DNA, resulting in a 15% higher DNA retention rate compared to the high-temperature group, indicating that FA can better maintain DNA stability. Our study suggests that using FA improves the immobilized DNA stability and amplification efficiency in SP-PCR.

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The nearest-neighbor (NN) model is a general tool for the evaluation for oligonucleotide thermodynamic stability. It is primarily used for the prediction of melting temperatures but has also found use in RNA secondary structure prediction and theoretical models of hybridization kinetics. One of the key problems is to obtain the NN parameters from melting temperatures, and VarGibbs was designed to obtain those parameters directly from melting temperatures. Here we will describe the basic workflow from RNA melting temperatures to NN parameters with the use of VarGibbs. We start by a brief revision of the basic concepts of RNA hybridization and of the NN model and then show how to prepare the data files, run the parameter optimization, and interpret the results.

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The Gd2O3 - GdSrFeO4 pseudo-binary phase diagram is presented for the first time. The liquidus and eutectic temperatures, metatectic points of the Gd2O3 transformations in the Gd2O3 - GdSrFeO4 section were defined using the Schröder-Le Chatelier equation, neglecting the effect of the isobaric heat capacity. The calculations were based on experimental data on the melting points of the end-members and the eutectic composition. From the results of phase relationships studies (subsolidus and high temperature region including literature data as well) and the above approach the Gd2O3-GdSrFeO4 pseudo-binary phase diagram in the temperature range 1400-2410 °C in air was constructed. It was shown that GdSrFeO4 of the K2NiF4- type is stable from 1100°Ð¡ to a congruent melting temperature of 1560°Ð¡ in air. The Gd2O3 - GdSrFeO4 system is eutectic with no intermediate compounds.

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Protein stability is a critical aspect of molecular biology and biochemistry, hinges on an intricate balance of thermodynamic and structural factors. Determining protein stability is crucial for understanding and manipulating biological machineries, as it directly correlated with the protein function. Thus, this study delves into the intricacies of protein stability, highlighting its dependence on various factors, including thermodynamics, thermal conditions, and structural properties. Moreover, a notable focus is placed on the free energy change of unfolding (ΔGunfolding), change in heat capacity (ΔCp) with protein structural transition, melting temperature (Tm) and number of disulfide bonds, which are critical parameters in understanding protein stability. In this study, a machine learning (ML) predictive model was developed to estimate these four parameters using the primary sequence of the protein. The shortfall of available tools for protein stability prediction based on multiple parameters propelled the completion of this study. Convolutional Neural Network (CNN) with multiple layers was adopted to develop a more reliable ML model. Individual predictive models were prepared for each property, and all the prepared models showed results with high accuracy. The R2 (coefficient of determination) of these models were 0.79, 0.78, 0.92 and 0.92, respectively, for ΔG, ΔCp, Tm and disulfide bonds. A case study on stability analysis of two homologous proteins was presented to validate the results predicted through the developed model. The case study included in silico analysis of protein stability using molecular docking and molecular dynamic simulations. This validation study assured the accuracy of each model in predicting the stability associated properties. The alignment of physics-based principles with ML models has provided an opportunity to develop a fast machine learning solution to replace the computationally demanding physics-based calculations used to determine protein stability. Furthermore, this work provided valuable insights into the impact of mutation on protein stability, which has implications for the field of protein engineering. The source codes are available at https://github.com/Growdeatechnology.

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In this study, the folding of G-quadruplex (G4) from the telomeric DNA sequences having loop nucleobases of different chemical natures, numbers, and arrangements in 10 mM and 100 mM KCl salt conditions mimicking the cancerous and normal KCl salt microenvironments have been investigated. The data suggest that the structure and stability of the G4 are highly dependent on the KCl salt concentration. In general, the conformational flexibility of the folded G4 is higher in KCl salt relevant to cancer than in the normal case for any loop arrangements with the same number of nucleobases. The stability of the G4 decreases with the increase in the number of loop nucleobases for both salt conditions. However, the decrease in the stability of G4 having adenine in the loop region is significantly higher than the case of thymine, particularly more prominent in the KCl salt relevant to the cancer. The topology of the folded G4 and its stability also depend delicately on the permutation of the nucleobases in the loop and the salt concentrations for a particular sequence. The findings indicate that the structure and stability of G4 are noticeably different in KCl salt relevant to physiological and cancer conditions.

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BACKGROUND: Time-dependent changes in cell populations during acute bacterial infections remain unclear. We assessed time-dependent changes in fluorescent light intensity of the neutrophil area (NE-SFL) and fluorescent light distribution width index of the neutrophil area (NE-WY) and their association with sepsis and bacteremia. METHODS: Patients with acute bacterial infections were enrolled in this prospective, observational cohort study. Blood samples were collected from all patients at the onset of bacterial infections (day 0) and on days 1 and 3. Microbiological evaluation included the examination of blood bacterial load using PCR. Cell population data were assessed using an automated hematology analyzer (Sysmex series XN-2000). RESULTS: Forty-three participants with acute bacterial infections were enrolled in the study. Twenty-five participants developed definite sepsis. All the participants improved after the onset of infection. NE-WY levels showed significant time-dependent changes in participants with sepsis, peaking on day 0 and significantly decreasing until day 3, whereas these changes were not statistically significant for NE-SFL. A significant correlation with the Sequential Organ Failure Assessment score was observed with NE-WY and NE-SFL in the entire cohort on days 0 and 1. However, only NE-WY showed a significant correlation with blood bacterial load on days 0 and 1. CONCLUSION: This study demonstrated that NE-WY elevation in sepsis peaked earlier than NE-SFL, which may partly reflect the early bacterial invasion into circulation. These findings advocate caution in interpreting cell population data values as sepsis biomarkers and propose the potential of NE-WY as a therapeutic indicator.

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Mastering selective molecule trafficking across human cell membranes poses a formidable challenge in healthcare biotechnology while offering the prospect of breakthroughs in drug delivery, gene therapy, and diagnostic imaging. The cholera toxin B-subunit (CTB) has the potential to be a useful cargo transporter for these applications. CTB is a robust protein that is amenable to reengineering for diverse applications; however, protein redesign has mostly focused on modifications of the N- and C-termini of the protein. Exploiting the full power of rational redesign requires a detailed understanding of the contributions of the surface residues to protein stability and binding activity. Here, we employed Rosetta-based computational saturation scans on 58 surface residues of CTB, including the GM1 binding site, to analyze both ligand-bound and ligand-free structures to decipher mutational effects on protein stability and GM1 affinity. Complimentary experimental results from differential scanning fluorimetry and isothermal titration calorimetry provided melting temperatures and GM1 binding affinities for 40 alanine mutants among these positions. The results showed that CTB can accommodate diverse mutations while maintaining its stability and ligand binding affinity. These mutations could potentially allow modification of the oligosaccharide binding specificity to change its cellular targeting, alter the B-subunit intracellular routing, or impact its shelf-life and in vivo half-life through changes to protein stability. We anticipate that the mutational space maps presented here will serve as a cornerstone for future CTB redesigns, paving the way for the development of innovative biotechnological tools.

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BACKGROUND: The accurate and expeditious detection of SARS-CoV-2 mutations is critical for monitoring viral evolution, assessing its impact on transmission, virulence, and vaccine efficacy, and formulating public health interventions. In this study, a detection system utilizing micro temperature gradient gel electrophoresis (µTGGE) was developed for the identification of the D614 and G614 variants of the SARS-CoV-2 spike protein. METHODS: The in vitro synthesized D614 and G614 gene fragments of the SARS-CoV-2 spike protein were amplified via polymerase chain reaction and subjected to µTGGE analysis. RESULTS: The migration patterns exhibited by the D614 and G614 variants on the polyacrylamide gel were distinctly dissimilar and readily discernible by µTGGE. In particular, the mid-melting pattern of D614 was shorter than that of G614. CONCLUSIONS: Our results demonstrate the capability of µTGGE for the rapid, precise, and cost-effective detection of SARS-CoV-2 spike protein D614 and G614 variants without the need for sequencing. Therefore, this approach holds considerable potential for use in point-of-care mutation assays for SARS-CoV-2 and other pathogens.

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Proteins are large biomolecules with a specific structure that is composed of one or more long amino acid chains. Correct protein structures are directly linked to their correct function, and many environmental factors can have either positive or negative effects on this structure. Thus, there is a clear need for methods enabling the study of proteins, their correct folding, and components affecting protein stability. There is a significant number of label-free methods to study protein stability. In this review, we provide a general overview of these methods, but the main focus is on fluorescence-based low-instrument and -expertise-demand techniques. Different aspects related to thermal shift assays (TSAs), also called differential scanning fluorimetry (DSF) or ThermoFluor, are introduced and compared to isothermal chemical denaturation (ICD). Finally, we discuss the challenges and comparative aspects related to these methods, as well as future opportunities and assay development directions.

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Adeno-associated virus (AAV) has shown great promise as a viral vector for gene therapy in clinical applications. The present work studied the effect of genome size on AAV production, purification, and thermostability by producing AAV2-GFP using suspension-adapted HEK293 cells via triple transfection using AAV plasmids containing the same GFP transgene with DNA stuffers for variable-size AAV genomes consisting of 1.9, 3.4, and 4.9 kb (ITR to ITR). Production was performed at the small and large shake flask scales and the results showed that the 4.9 kb GFP genome had significantly reduced encapsidation compared to other genomes. The large shake flask productions were purified by AEX chromatography, and the results suggest that the triple transfection condition significantly affects the AEX retention time and resolution between the full and empty capsid peaks. Charge detection-mass spectrometry was performed on all AEX full-capsid peak samples showing a wide distribution of empty, partial, full length, and copackaged DNA in the capsids. The AEX-purified samples were then analyzed by differential scanning fluorimetry, and the results suggest that sample formulation may improve the thermostability of AAV genome ejection melting temperature regardless of the packaged genome content.

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Introduction: The level of fatty acid unsaturation in seeds is one of the major determinants of cold germination ability, particularly in oilseeds. The presence of cis double bonds in unsaturated fatty acids creates bends that lowers their melting temperatures compared to saturated fatty acids. Unsaturated fatty acids with low melting points mobilize faster at low temperatures providing seeds with sufficient energy for germination. Methodology: To investigate the effects of fatty acid unsaturation on the ability of cotton seeds to germinate under cold conditions, four recombinant inbred lines (RILs) of cotton with unique fatty acid profiles were evaluated using a set of developmental and biochemical assays at 12°C (critically low temperature), 15°C (cardinal minimum temperature) and 30°C (optimum temperature). Furthermore, whole seed lipidome profiling using liquid chromatography with mass spectrometry was done to compare the lipid compositional changes at 12°C and 30°C after imbibing cotton seeds of all the six genotypes for 0 hours, 3 hours and 6 hours. Results and discussion: The RILs with higher unsaturation/saturation ratios registered robust germination performance, lower solute leakage, and optimum water uptake rates under cold stress. Imbibition at 30°C for 8 hours before cold exposure significantly improved the germination of cold sensitive genotypes, indicating that the first few hours of water uptake are critical for cold stress. Whole seed lipidome profiling of all the genotypes specifically associated cold germination ability with higher unsaturation levels of phospholipids during early imbibition. The presence of cis double bonds in phospholipids creates kinks that maintain the fluidity of cell membranes under low temperature. Membrane flexibility under cold conditions is essential for facilitating key germination events including membrane organization and respiration. The current results highlight the importance of fatty acid composition in cold germination ability of upland cotton.

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Thermally stable proteins find extensive applications in industrial production, pharmaceutical development, and serve as a highly evolved starting point in protein engineering. The thermal stability of proteins is commonly characterized by their melting temperature (Tm). However, due to the limited availability of experimentally determined Tm data and the insufficient accuracy of existing computational methods in predicting Tm, there is an urgent need for a computational approach to accurately forecast the Tm values of thermophilic proteins. Here, we present a deep learning-based model, called DeepTM, which exclusively utilizes protein sequences as input and accurately predicts the Tm values of target thermophilic proteins on a dataset consisting of 7790 thermophilic protein entries. On a test set of 1550 samples, DeepTM demonstrates excellent performance with a coefficient of determination (R2) of 0.75, Pearson correlation coefficient (P) of 0.87, and root mean square error (RMSE) of 6.24 ℃. We further analyzed the sequence features that determine the thermal stability of thermophilic proteins and found that dipeptide frequency, optimal growth temperature (OGT) of the host organisms, and the evolutionary information of the protein significantly affect its melting temperature. We compared the performance of DeepTM with recently reported methods, ProTstab2 and DeepSTABp, in predicting the Tm values on two blind test datasets. One dataset comprised 22 PET plastic-degrading enzymes, while the other included 29 thermally stable proteins of broader classification. In the PET plastic-degrading enzyme dataset, DeepTM achieved RMSE of 8.25 ℃. Compared to ProTstab2 (20.05 ℃) and DeepSTABp (20.97 ℃), DeepTM demonstrated a reduction in RMSE of 58.85% and 60.66%, respectively. In the dataset of thermally stable proteins, DeepTM (RMSE=7.66 ℃) demonstrated a 51.73% reduction in RMSE compared to ProTstab2 (RMSE=15.87 ℃). DeepTM, with the sole requirement of protein sequence information, accurately predicts the melting temperature and achieves a fully end-to-end prediction process, thus providing enhanced convenience and expediency for further protein engineering.

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This study aims to establish a rapid identification method based on the Proofman-LMTIA technique for distinguishing between Panax quinquefolium and Panax ginseng. By targeting specific 18S rDNA sequences, suitable primers and Proofman probes labeled FAM or JOE were designed for LMTIA. Initially, single-species-primer Proofman-LMTIA assays were performed separately for each ginseng type to optimize reaction temperature, assess sensitivity and specificity, and determine the detection limit. Subsequently, both sets of primers and their corresponding probes were combined in the same reaction system to further optimize reaction conditions, evaluate sensitivity, and assess stability. Finally, the developed Proofman-duplex-LMTIA technique was employed to detect P. quinquefolium and P. ginseng slices available in the market. Single-plex Proofman-LMTIA assays revealed that the optimal reaction temperature for both P. quinquefolium and P. ginseng was 62 °C. The sensitivity was as low as 1 pg/µL, with a detection limit of 0.1%, and both showed excellent specificity. The optimal temperature for Proofman-duplex-LMTIA assays was 58 °C. This method could simultaneously identify P. quinquefolium and P. ginseng. Testing 6 samples of P. ginseng and 11 samples of P. quinquefolium from the market resulted in a 100% positive rate for all samples. This study successfully established a rapid, simple, sensitive, and specific Proofman-duplex-LMTIA identification method for P. quinquefolium and P. ginseng. It provides an effective means for quality control of P. quinquefolium, P. ginseng, and related products.

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In-plane hybrid graphene/hexagonal boron nitride (h-BN) heterostructure (graphene/hBN/graphene) is studied via molecular dynamics simulation. The initial configuration (6400-atom graphene/6200-atom h-BN/6400-atom graphene) is heated up from 50 K to 7500 K via Tersoff potential. To study the structural evolution, some thermal dynamics quantities are calculated such as the coordination number, the total energy per atom, the heat capacity, the angular distribution, and the distribution of rings. Some main results are calculated and presented as follows: i) The sudden increase of total energy per atom at the melting point (5500 K) exhibits the first order phase transition from the crystalline state to a liquid state of the hybrid graphene/h-BN/graphene heterostructure; ii) The heat capacity shows two peaks. The first peak (at 5500 K) represents the phase transition from the crystalline to a liquid states while the second one (at 6300 K) represents the formation of gaseous atoms of B and N in the h-BN sheet; iii) The coordination number of three decreases dramatically at temperature of 5500 K (about 10% lefts for each type of atoms) leading to the formation of the first peak in the graph of the heat capacity. The coordination number of zero for B and N in the h-BN layer increases significantly (over 55%) at 6300 K causing the formation of the second peak in the graph of the heat capacity; iv) The influence of the relative number of atoms of h-BN to graphene in the hybrid graphene/h-BN/graphene heterostructure on the structural evolution upon heating is considered as follows. The number of atoms in the graphene sheets remains constant (6400 atoms per sheet) while the one of the h-BN sheet varies in size (780, 1560, 3120, 4680, 5490, 5880, 6080, and 6200 atoms). The results show that although the phase transition is still the first order type, the phase transition temperature decreases as the size of the h-BN layer in the hybrid heterostructure increases.

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Microbial factors, including bacteria, viruses, and other pathogens, are significant contributors to foodborne illnesses, posing serious food safety risks due to their potential for rapid growth and contamination. Listeria monocytogenes is one of the most common types of foodborne bacteria that can cause serious foodborne diseases or even fatalities. In this study, a novel nucleic acid amplification method called Proofman-LMTIA was employed to detect Listeria monocytogenes contamination in food. This method combines proofreading enzyme-mediated probe cleavage with ladder-shape melting temperature isothermal amplification. A positive recombinant plasmid was used as a control to ensure the accuracy of the detection results, and primers and Proofman probes were specifically designed for the LMTIA. Genomic DNA was extracted, the reaction temperature was optimized, and the primers' specificity was verified using foodborne pathogens like Staphylococcus aureus, Escherichia coli O157:H7, and Salmonella. The sensitivity was assessed by testing serial dilutions of genomic DNA, and the method's applicability was confirmed by detecting artificially contaminated fresh pork. The established LMTIA method exhibited both high specificity and sensitivity. At the optimal reaction temperature of 63 °C, the primers specifically identified Listeria monocytogenes contamination in pork at a concentration of 8.0 ± 0.7 colony-forming units (CFUs) per 25 g. Furthermore, the Proofman-LMTIA method was applied to test Listeria monocytogenes DNA in 30 food samples purchased from a Chinese retail market, and reassuringly, all results indicated no contamination. Proofman-LMTIA can serve as a reliable and rapid method for detecting Listeria monocytogenes in food, contributing to public health by safeguarding consumers from foodborne illnesses, and strengthening food safety regulations.

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