Protein Chain Research Articles

Trans-cinnamaldehyde fumigation inhibits Escherichia coli by affecting the mechanism of intracellular biological macromolecules

This study aimed to determine the antibacterial mechanism of cinnamaldehyde fumigation in Escherichia coli (E. coli). Through vapour fumigation, cinnamaldehyde was confirmed to exhibit effective antibacterial activity against E. coli. The minimum inhibitory concentration (MIC) and minimum bacterial concentration (MBC) were 0.25 μL/mL and 0.5 μL/mL, respectively. Based on transmission electron microscopy, the wrinkled bacterial cells observed after fumigation could be related to the leakage of intracellular substances. Laser tweezers Raman spectroscopy revealed changes in the main chain of proteins, the hydrogen bond system and spatial structure, and single- and double-stranded DNA breaks. In addition, breakage of the fatty acyl chain backbone was found to affect the vertical order degree of the lipid bilayer and cell membrane fluidity, thereby inhibiting the growth of E. coli. Overall, our findings indicate that cinnamaldehyde fumigation inhibits E. coli growth by inducing changes in intracellular biological macromolecules.

The impact of exercise on blood-based biomarkers of Alzheimer's disease in cognitively unimpaired older adults.

Physical activity is a promising preventative strategy for Alzheimer's disease: it is associated with lower dementia risk, better cognition, greater brain volume and lower brain beta-amyloid. Blood-based biomarkers have emerged as a low-cost, non-invasive strategy for detecting preclinical Alzheimer's disease, however, there is limited literature examining the effect of exercise (a structured form of physical activity) on blood-based biomarkers. The current study investigated the influence of a 6-month exercise intervention on levels of plasma beta-amyloid (Aβ42, Aβ40, Aβ42/40), phosphorylated tau (p-tau181), glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) chain in cognitively unimpaired older adults, and as a secondary aim, whether blood-based biomarkers related to cognition. Ninety-nine community-dwelling older adults (69.1 ± 5.2) were allocated to an inactive control, or to moderate or high intensity exercise groups where they cycled twice weekly for six months. At baseline and six months (post-intervention), fasted blood was collected and analysed using single molecule array (SIMOA) assays, and cognition was assessed. Results demonstrated no change in levels of any plasma biomarker from pre- to post-intervention. At baseline, higher NfL was associated with poorer cognition (β = -0.33, SE = 0.13, adjusted p = .042). Exploratory analyses indicated higher cardiorespiratory fitness was associated with higher NfL and GFAP levels in apolipoprotein E (APOE) ε4 non-carriers compared to ε4 carriers (NfL, β = -0.43, SE = 0.19, p = .029; GFAP, β = -0.41, SE = 0.20, p = .044), though this association was mediated by body mass index (BMI). These results highlight the importance of considering BMI in analysis of blood-based biomarkers, especially when investigating differences between APOE ε4 carriers and non-carriers. Our results also indicate that longer follow-up periods may be required to observe exercise-induced change in blood-based biomarkers.

A novel data augmentation approach for influenza A subtype prediction based on HA proteins

Influenza, a pervasive viral respiratory illness, remains a significant global health concern. The influenza A virus, capable of causing pandemics, necessitates timely identification of specific subtypes for effective prevention and control, as highlighted by the World Health Organization. The genetic diversity of influenza A virus, especially in the hemagglutinin protein, presents challenges for accurate subtype prediction. This study introduces PreIS as a novel pipeline utilizing advanced protein language models and supervised data augmentation to discern subtle differences in hemagglutinin protein sequences. PreIS demonstrates two key contributions: leveraging pre-trained protein language models for influenza subtype classification and utilizing supervised data augmentation to generate additional training data without extensive annotations. The effectiveness of the pipeline has been rigorously assessed through extensive experiments, demonstrating a superior performance with an impressive accuracy of 94.54% compared to the current state-of-the-art model, the MC-NN model, which achieves an accuracy of 89.6%. PreIS also exhibits proficiency in handling unknown subtypes, emphasizing the importance of early detection. Pioneering the classification of HxNy subtypes solely based on the hemagglutinin protein chain, this research sets a benchmark for future studies. These findings promise more precise and timely influenza subtype prediction, enhancing public health preparedness against influenza outbreaks and pandemics. The data and code underlying this article are available in https://github.com/CBRC-lab/PreIS.

Graph-theoretical prediction of biological modules in quaternary structures of large protein complexes.

The functional complexity of biochemical processes is strongly related to the interplay of proteins and their assembly into protein complexes. In recent years, the discovery and characterization of protein complexes have substantially progressed through advances in cryo-electron microscopy, proteomics, and computational structure prediction. This development results in a strong need for computational approaches to analyse the data of large protein complexes for structural and functional characterization. Here, we aim to provide a suitable approach, which processes the growing number of large protein complexes, to obtain biologically meaningful information on the hierarchical organization of the structures of protein complexes. We modelled the quaternary structure of protein complexes as undirected, labelled graphs called complex graphs. In complex graphs, the vertices represent protein chains and the edges spatial chain-chain contacts. We hypothesized that clusters based on the complex graph correspond to functional biological modules. To compute the clusters, we applied the Leiden clustering algorithm. To evaluate our approach, we chose the human respiratory complex I, which has been extensively investigated and exhibits a known biological module structure experimentally validated. Additionally, we characterized a eukaryotic group II chaperonin TRiC/CCT and the head of the bacteriophage Φ29. The analysis of the protein complexes correlated with experimental findings and indicated known functional, biological modules. Using our approach enables not only to predict functional biological modules in large protein complexes with characteristic features but also to investigate the flexibility of specific regions and coformational changes. The predicted modules can aid in the planning and analysis of experiments. Jupyter notebooks to reproduce the examples are available on our public GitHub repository: https://github.com/MolBIFFM/PTGLtools/tree/main/PTGLmodulePrediction.

THE INFLUENCE OF STARCH PRODUCTS ON THE RHEOLOGI-CAL, PHYSICAL AND CHEMICAL PROPERTIES OF YOGURT

Expanding the assortment of low-fat yogurt with natural structuring sweeteners and regulated quality indicators is an actual direction of scientific research. The purpose of the study is to study the patterns of influence of the products of enzymatic hydrolysis of corn starch with different dextrose equivalents on the rheological, physical and chemical characteristics of yogurt. Тhe functional and technological properties of starch products of different chemical composition were studied – maltodextrin MD-10, glucose syrup IG-42 and glucose-fructose syrup GFS-42. The possibility of completely replacing dry skimmed milk and sugar in the composition of yogurt with a fat content of 1% drinkable with an equivalent content of dry substances of maltodextrin MD-10 and glucose syrup IG-42, which ensure the formation of rheological characteristics inherent high-quality yogurt. Yogurt with sucrose, which inhibits the organization of macromolecular chains of milk proteins, has the lowest thixotropic ability, and yogurt with maltodextrin MD-10 and glucose syrup IG-42 has the highest. The predominance of higher sugars in the composition of MD-10 maltodextrin lengthens, and the increased content of monosaccharides in GFS-42 accelerates the duration of fermentation of milk mixtures in the technological process of production of yogurt with a fat content of 1.0%. Monosaccharides in the composition of GFS-42 significantly affect the activity of water and at the same time reduce the moisture-retaining capacity of the sour-milk yogurt curd. The degree of influence on the rheological characteristics and moisture-binding capacity of yogurt increases with a decrease in the dextrose equivalent of starch products in the following sequence: GFS-42 → IG-42 → MD-10. So, it is the dextrose equivalent of starch products that is an objective criterion of their technological activity as part of yogurt. The results of the study will allow purposeful management of the process of forming low-fat yogurt quality indicators.

Cysteine Is the Only Universally Affected and Disfavored Proteomic Amino Acid under Oxidative Conditions in Animals.

Oxidative modifications of amino acid side chains in proteins are a hallmark of oxidative stress, and they are usually regarded as structural damage. However, amino acid oxidation may also have a protective effect and may serve regulatory or structural purposes. Here, we have attempted to characterize the global redox role of the 20 proteinogenic amino acids in animals by analyzing their usage frequency in 5 plausible evolutionary paradigms of increased oxidative burden: (i) peroxisomal proteins versus all proteins, (ii) mitochondrial proteins versus all proteins, (iii) mitochondrially encoded respiratory chain proteins versus all mitochondrial proteins, (iv) proteins from long-lived animals versus those from short-lived animals, and (v) proteins from aerobic, free-living animals versus those from facultatively anaerobic animals. We have found that avoidance of cysteine in the oxidative condition was the most pronounced and significant variation in the majority of comparisons. Beyond this preeminent pattern, only local signals were observed, primarily increases in methionine and glutamine as well as decreases in serine and proline. Hence, certain types of cysteine oxidation appear to enforce its proteome-wide evolutionary avoidance despite its essential role in disulfide bond formation and metal ligation. The susceptibility to oxidation of all other amino acids appears to be generally unproblematic, and sometimes advantageous.

Diffusive dynamics of a model protein chain in solution.

A Markov state model is a powerful tool that can be used to track the evolution of populations of configurations in an atomistic representation of a protein. For a coarse-grained linear chain model with discontinuous interactions, the transition rates among states that appear in the Markov model when the monomer dynamics is diffusive can be determined by computing the relative entropy of states and their mean first passage times, quantities that are unchanged by the specification of the energies of the relevant states. In this paper, we verify the folding dynamics described by a diffusive linear chain model of the crambin protein in three distinct solvent systems, each differing in complexity: a hard-sphere solvent, a solvent undergoing multi-particle collision dynamics, and an implicit solvent model. The predicted transition rates among configurations agree quantitatively with those observed in explicit molecular dynamics simulations for all three solvent models. These results suggest that the local monomer-monomer interactions provide sufficient friction for the monomer dynamics to be diffusive on timescales relevant to changes in conformation. Factors such as structural ordering and dynamic hydrodynamic effects appear to have minimal influence on transition rates within the studied solvent densities.

Hierarchical Assembly of Single-Stranded RNA.

Single-stranded RNA (ssRNA) plays a major role in the flow of genetic information-most notably, in the form of messenger RNA (mRNA)-and in the regulation of biological processes. The highly dynamic nature of chains of unpaired nucleobases challenges structural characterizations of ssRNA by experiments or molecular dynamics (MD) simulations alike. Here, we use hierarchical chain growth (HCG) to construct ensembles of ssRNA chains. HCG assembles the structures of protein and nucleic acid chains from fragment libraries created by MD simulations. Applied to homo- and heteropolymeric ssRNAs of different lengths, we find that HCG produces structural ensembles that overall are in good agreement with diverse experiments, including nuclear magnetic resonance (NMR), small-angle X-ray scattering (SAXS), and single-molecule Förster resonance energy transfer (FRET). The agreement can be further improved by ensemble refinement using Bayesian inference of ensembles (BioEn). HCG can also be used to assemble RNA structures that combine base-paired and base-unpaired regions, as illustrated for the 5' untranslated region (UTR) of SARS-CoV-2 RNA.

Hygrothermal ageing of dry gelatine adhesive films: Microstructure-property relationships

Gelatine adhesives, also known as animal glues, are collagen-based water-soluble biopolymers derived from vertebrate connective tissues. One of the various fields in which gelatine adhesives are widely used is the conservation of cultural heritage such as decorated furniture and panel paintings. It is observed that, with time, the failure in these objects often occurs along the adhesive bondlines. Given the moisture and temperature sensitivity of these adhesives, obtaining knowledge of their long-term behaviour, when exposed to climate variations, is pivotal. Here, the influence of hygrothermal ageing (exposure to a combination of elevated temperature and relative humidity (RH) cycling) on the microstructure and macroscopic properties of four different types of gelatine adhesives is investigated. These adhesives were selected from different animal origins namely bovine, rabbit, and fish with different Bloom strengths. It was observed that ageing cycles interfere with the most critical structural feature of protein chains namely triple helices. A clear decay in triple helix content at the micro-scale, determined by Differential Scanning Calorimetry (DSC) and X-Ray Diffraction (XRD) techniques, was observed which had implications on the macroscopic properties of these adhesives such as reduction of strain to failure and toughness (strain energy density to failure). The rate of decay in properties was revealed to be the highest in the adhesives with the lowest triple helix content. This study provides a scientific view of microstructure-property relationships in gelatinous adhesives as a function of environmental ageing, and stipulates the underlying mechanism of the degradation of mechanical properties as the loss of structural triple helices, regardless of the animal origin.

The effects of short-term, progressive exercise training on disease activity in smouldering multiple myeloma and monoclonal gammopathy of undetermined significance: a single-arm pilot study.

High levels of physical activity are associated with reduced risk of the blood cancer multiple myeloma (MM). MM is preceded by the asymptomatic stages of monoclonal gammopathy of undetermined significance (MGUS) and smouldering multiple myeloma (SMM) which are clinically managed by watchful waiting. A case study (N = 1) of a former elite athlete aged 44 years previously indicated that a multi-modal exercise programme reversed SMM disease activity. To build from this prior case study, the present pilot study firstly examined if short-term exercise training was feasible and safe for a group of MGUS and SMM patients, and secondly investigated the effects on MGUS/SMM disease activity. In this single-arm pilot study, N = 20 participants diagnosed with MGUS or SMM were allocated to receive a 16-week progressive exercise programme. Primary outcome measures were feasibility and safety. Secondary outcomes were pre- to post-exercise training changes to blood biomarkers of MGUS and SMM disease activity- monoclonal (M)-protein and free light chains (FLC)- plus cardiorespiratory and functional fitness, body composition, quality of life, blood immunophenotype, and blood biomarkers of inflammation. Fifteen (3 MGUS and 12 SMM) participants completed the exercise programme. Adherence was 91 ± 11%. Compliance was 75 ± 25% overall, with a notable decline in compliance at intensities > 70% V̇O2PEAK. There were no serious adverse events. There were no changes to M-protein (0.0 ± 1.0g/L, P =.903), involved FLC (+ 1.8 ± 16.8mg/L, P =.839), or FLC difference (+ 0.2 ± 15.6mg/L, P =.946) from pre- to post-exercise training. There were pre- to post-exercise training improvements to diastolic blood pressure (- 3 ± 5 mmHg, P =.033), sit-to-stand test performance (+ 5 ± 5 repetitions, P =.002), and energy/fatigue scores (+ 10 ± 15%, P =.026). Other secondary outcomes were unchanged. A 16-week progressive exercise programme was feasible and safe, but did not reverse MGUS/SMM disease activity, contrasting a prior case study showing that five years of exercise training reversed SMM in a 44-year-old former athlete. Longer exercise interventions should be explored in a group of MGUS/SMM patients, with measurements of disease biomarkers, along with rates of disease progression (i.e., MGUS/SMM to MM). https://www.isrctn.com/ISRCTN65527208 (14/05/2018).

Puromycin reveals a distinct conformation of neuronal ribosomes

Puromycin is covalently added to the nascent chain of proteins by the peptidyl transferase activity of the ribosome and the dissociation of the puromycylated peptide typically follows this event. It was postulated that blocking the translocation of the ribosome with emetine could retain the puromycylated peptide on the ribosome, but evidence against this has recently been published [Hobson et al., Elife 9, e60048 (2020); and Enam et al., Elife 9, e60303 (2020)]. In neurons, puromycylated nascent chains remain in the ribosome even in the absence of emetine, yet direct evidence for this has been lacking. Using biochemistry and cryoelectron microscopy, we show that the puromycylated peptides remain in the ribosome exit channel in the large subunit in a subset of neuronal ribosomes stalled in the hybrid state. These results validate previous experiments to localize stalled polysomes in neurons and provide insight into how neuronal ribosomes are stalled. Moreover, in these hybrid-state neuronal ribosomes, anisomycin, which usually blocks puromycylation, competes poorly with puromycin in the puromycylation reaction, allowing a simple assay to determine the proportion of nascent chains that are stalled in this state. In early hippocampal neuronal cultures, over 50% of all nascent peptides are found in these stalled polysomes. These results provide insights into the stalling mechanisms of neuronal ribosomes and suggest that puromycylated peptides can be used to reveal subcellular sites of hybrid-state stalled ribosomes in neurons.

Metabolomics and Physiological Methods Revealed the Effects of Drought Stress on the Quality of Broomcorn Millet during the Flowering Stage

The flowering stage is a critical period for water sensitivity and quality formation of broomcorn millets. However, the effects and mechanisms of drought stress on the quality formation of broomcorn millets are not clear. We used the drought-resistant variety Hequ red millet (H) and the drought-sensitive variety Yanshu No. 10 (Y) were used as materials for drought stress treatment during the flowering stage, metabolomics and physiological methods were used to study the differences in protein, starch, amino acids, medium and medium-long chain fatty acids, and their response characteristics to drought in broomcorn millet. The results showed that different genotypes of broomcorn millets exhibited different response mechanisms in the face of drought stress. In Hequ red millet, drought stress significantly increased the contents of amylopectin (2.57%), pyridoxine (31.89%), and anthocyanin, and significantly decreased the contents of water-soluble protein (5.82%), glutelin (10.07%), thiamine (14.95%) and nicotinamide (23.01%). In Yanshu No. 10, drought significantly decreased amylose by 6.05%, and significantly increased riboflavin and nicotinamide contents by 21.11% and 32.59%. Correlation analysis showed that total starch and amylose were highly significantly positively correlated with methyl palmitate; negatively correlated with amylopectin, vitamins, proteins, free amino acids, and medium-long chain fatty acids; and amylopectin was significantly positively correlated with water-soluble protein, riboflavin, and pyridoxine. Water-soluble protein and glutelin were significantly positively correlated with most free amino acids, medium-long chain fatty acids, and nicotinamide. Thiamine showed significant positive correlation with nicotinamide and significant negative correlation with pyridoxine. Riboflavin was significantly positively correlated with nicotinamide, pyridoxine, and water-soluble protein, and pyridoxine was significantly positively correlated with water-soluble protein. Hequ red millet transforms into amylopectin by consuming water-soluble protein and glutelin, and improves drought resistance by accumulating pyridoxine, and changes its physicochemical properties by decreasing the content of amylose and protein and elevating the content of amylopectin. Yanshu No. 10 resisted drought by catabolizing lipids to produce fatty acids and by consuming amylose for conversion into other metabolites. The present study helps to understand the response of the nutritional quality of millets to drought stress at the flowering stage and provides a theoretical basis for the selection and breeding of superior varieties of millets and drought resistance research.

ULDNA: integrating unsupervised multi-source language models with LSTM-attention network for high-accuracy protein-DNA binding site prediction.

Efficient and accurate recognition of protein-DNA interactions is vital for understanding the molecular mechanisms of related biological processes and further guiding drug discovery. Although the current experimental protocols are the most precise way to determine protein-DNA binding sites, they tend to be labor-intensive and time-consuming. There is an immediate need to design efficient computational approaches for predicting DNA-binding sites. Here, we proposed ULDNA, a new deep-learning model, to deduce DNA-binding sites from protein sequences. This model leverages an LSTM-attention architecture, embedded with three unsupervised language models that are pre-trained on large-scale sequences from multiple database sources. To prove its effectiveness, ULDNA was tested on 229 protein chains with experimental annotation of DNA-binding sites. Results from computational experiments revealed that ULDNA significantly improves the accuracy of DNA-binding site prediction in comparison with 17 state-of-the-art methods. In-depth data analyses showed that the major strength of ULDNA stems from employing three transformer language models. Specifically, these language models capture complementary feature embeddings with evolution diversity, in which the complex DNA-binding patterns are buried. Meanwhile, the specially crafted LSTM-attention network effectively decodes evolution diversity-based embeddings as DNA-binding results at the residue level. Our findings demonstrated a new pipeline for predicting DNA-binding sites on a large scale with high accuracy from protein sequence alone.

Testosterone synthesis was inhibited in the testis metabolomics of a depression mouse model

IntroductionDepression is a common emotional disorder. Previous studies have suggested that depression is associated with the central nervous system. Recent studies have suggested that reduced testosterone level is the core inducement of depression. Testis is the vital organ for the synthesis of testosterone. How does testis mediate depression is still unknown. ObjectivesWe adopted a classical depression model of mouse caused through chronic mild stress (CMS). The metabolomics liquid chromatography-mass spectrometry was adopted to analyse the influence of CMS on testis metabolism. Then we confirmed the possible abnormal metabolism of the testis in depression mice by pathway analysis and molecular biological technique. ResultsCompared with control mice, 16 differential metabolites were found in CMS mice by multivariate statistical analysis. In comparison with control mice, CMS mice showed higher levels for campesterol, ribitol, citric acid, platelet activating factor, guanosine, cytosine and xanthine and lower levels for docosahexaenoic acid, hippuric acid, creatine, testosterone, dehydroepiandrosterone, progesterone, l-carnitine, acetyl carnitine and propionyl carnitine. The pathway analysis indicated that these differential metabolites are associated with steroid hormone synthesis, purine metabolism and phenylalanine metabolism. In addition, we also first discovered that testicular morphology in depression mice was damaged and steroid hormone synthetases (including steroidogenic acute regulatory protein and P450 cholesterol side chain cleavage) were inhibited. ConclusionThese findings may be helpful to parse molecular mechanisms of pathophysiology of depression. It also pointed out the direction to search for potential therapy schedules for male depression and provide novel insights into exploring the pathogenesis of male depression.

Combining Glial Fibrillary Acidic Protein and Neurofilament Light Chain for the Diagnosis of Major Depressive Disorder.

Major depressive disorder (MDD) is a prevalent brain disorder affecting more than 2% of the world's population. Due to the lack of well-specific biomarkers, it is difficult to distinguish MDD from other diseases with similar clinical symptoms (such as Alzheimer's disease and cerebral thrombosis). In this work, we provided a strategy to address this issue by constructing a combinatorial biomarker of serum glial fibrillary acidic protein (GFAP) and neurofilament light chain (NFL). To achieve the convenient and sensitive detection of two proteins, we developed an electrochemical immunosandwich sensor using two metal-ion-doped carbon dots (Pb-CDs and Cu-CDs) as probes for signal output. Each probe contains approximately 300 Pb2+ or 200 Cu2+, providing excellent signal amplification. This method achieved detection limits of 0.3 pg mL-1 for GFAP and 0.2 pg mL-1 for NFL, lower than most of the reported detection limits. Analysis of real serum samples showed that the concentration ratio of GFAP to NFL, which is associated with the relative degree of brain inflammation and neurodegeneration, is suitable for not only distinguishing MDD from healthy individuals but also specifically distinguishing MDD from Alzheimer's disease and cerebral thrombosis. The good specificity gives the combinatorial GFAP/NFL biomarker broad application prospects in the screening, diagnosis, and treatment of MDD.

Q-BioLiP: A Comprehensive Resource for Quaternary Structure-based Protein-ligand Interactions.

Since its establishment in 2013, BioLiP has become one of the widely used resources for protein-ligand interactions. Nevertheless, several known issues occurred with it over the past decade. For example, the protein-ligand interactions are represented in the form of single chain-based tertiary structures, which may be inappropriate as many interactions involve multiple protein chains (known as quaternary structures). We sought to address these issues, resulting in Q-BioLiP, a comprehensive resource for quaternary structure-based protein-ligand interactions. The major features of Q-BioLiP include: (1) representing protein structures in the form of quaternary structures rather than single chain-based tertiary structures; (2) pairing DNA/RNA chains properly rather than separation; (3) providing both experimental and predicted binding affinities; (4) retaining both biologically relevant and irrelevant interactions to alleviate the wrong justification of ligands' biological relevance; and (5) developing a new quaternary structure-based algorithm for the modelling of protein-ligand complex structure. With these new features, Q-BioLiP is expected to be a valuable resource for studying biomolecule interactions, including protein-small molecule interaction, protein-metal ion interaction, protein-peptide interaction, protein-protein interaction, protein-DNA/RNA interaction, and RNA-small molecule interaction. Q-BioLiP is freely available at https://yanglab.qd.sdu.edu.cn/Q-BioLiP/.

P75NTR regulates autophagy through the YAP-mTOR pathway to increase the proliferation of interfollicular epidermal cells and promote wound healing in diabetic mice

Wound healing is delayed in diabetic patients. Increased autophagy and dysfunction of interfollicular epidermal (IFE) cells are closely associated with delayed healing of diabetic wounds. Autophagy plays an important role in all stages of wound healing, but its role in diabetic wound healing and the underlying molecular mechanisms are not clear. Here, we found that diabetic mice had delayed wound healing and increased autophagy in wounds compared with normal mice and that chloroquine, an inhibitor of autophagy, decreased the level of autophagy, improved the function of IFE cells, and accelerated wound healing in diabetic mice. Treatment of IFE cells with advanced glycosylation end products (AGEs) resulted in increased microtubule-associated protein chain (LC3) expression and decreased prostacyclin-62 (P62) expression, indicating increased autophagy in AGE-treated IFE cells. Moreover, P75NTR reduced autophagy in IFE cells in the presence of AGEs and significantly increased the proliferation of IFE cells. In addition, P75NTR participated in regulating autophagy in IFE cells and in wounds in diabetic mice through the YAP-mTOR signalling pathway, which increased the functional activity of the cells and the healing rate of wounds in diabetic mice. Thus, our study suggests that P75NTR protects IFE cells against AGEs by affecting autophagy and accelerating wound healing in diabetic mice, providing a basis for understanding the role of autophagy in diabetic wound healing.

The beginning study of transglutaminase from plant origin

Texture is an important parameter in processed foods such as meatball, sausage and surimi, where it is affected by the protein gel strength. Sodium tripolyphosphate is often used to improve quality of food texture, and even borax which is harmful to health including causing severe dizziness and trouble breathing, is still widely used. This study aims to explore and characterize transglutaminase of plant origin which is safer than gelling chemicals agents in food products. Transglutaminase is an enzime that can modify protein into strong gel by creating cross-linkage among protein chains. Animal tissue is one source of transglutaminase but requires high costs for providing raw materials. While the search for transglutaminase source from microorganisms need many stages to ensure that transglutaminase meets safety standards, therefore transglutaminasefrom plant origin is an alternative. The method in this study was to identify and characterize transglutaminase extracted from iodine leaf (Jatropha multifida), including determining the optimum temperature, optimum pH as well as activator and inhibitor of transglutaminase extract from iodine leaf. The results showed that the optimum temperature for transglutaminase from iodine leaf is 40-60 oC; The optimum pH is in the range of 6-7. Unlike most transglutaminases derived from animal tissues, transglutaminase from iodine leaf does not depent on presence of Ca2+, however Zn2+ could be an inhibitor. Transglutaminase extract from iodine leaf has high activity, it will be a promising potential to be applied in food industry to improve texture quality.

Salt-bridge mediated conformational dynamics in the figure-of-eight knotted ketol acid reductoisomerase (KARI).

The utility of knotted proteins in biological activities has been ambiguous since their discovery. From their evolutionary significance to their functionality in stabilizing the native protein structure, a unilateral conclusion hasn't been achieved yet. While most studies have been performed to understand the stabilizing effect of the knotted fold on the protein chain, more ideas are yet to emerge regarding the interactions in stabilizing the knot. Using classical molecular dynamics (MD) simulations, we have explored the dynamics of the figure-of-eight knotted domain present in ketol acid reductoisomerase (KARI). Our main focus was on the presence of a salt bridge network evident within the knotted region and its role in shaping the conformational dynamics of the knotted chain. Through the potential of mean forces (PMFs) calculation, we have also marked the specific salt bridges that are pivotal in stabilizing the knotted structure. The correlated motions have been further monitored with the help of principal component analysis (PCA) and dynamic cross-correlation maps (DCCM). Furthermore, mutation of the specific salt bridges led to a change in their conformational stability, vindicating their importance.

Serum Biomarker Profiles Discriminate AQP4 Seropositive and Double Seronegative Neuromyelitis Optica Spectrum Disorder.

Glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) serum levels are useful to define disease activity in different neurologic conditions. These biomarkers are increased in patients with aquaporin-4 antibody-positive NMOSD (AQP4+NMOSD) during clinical attacks suggesting a concomitant axonal and glial damage. However, there are contradictory results in double seronegative NMOSD (DS-NMOSD). The aim of this study was to characterize the neuronal, axonal, and glial damage of DS-NMOSD in comparison with AQP4+NMOSD. Patients with DS-NMOSD (i.e., for AQP4 and myelin oligodendrocyte glycoprotein antibodies-MOG-Abs) and age-matched AQP4+NMOSD diagnosed according to the latest diagnostic criteria and with available serum samples obtained within 3 months from onset/relapse were retrospectively enrolled from 14 international centers. Clinical and radiologic data were collected. Serum NfL, GFAP, tau, and UCH-L1 levels were determined using an ultrasensitive paramagnetic bead-based ELISA (SIMOA). Statistical analysis was performed using nonparametric tests and receiver-operating characteristic (ROC) curve analysis. We included 25 patients with AQP4+NMOSD and 26 with DS-NMOSD. The median age at disease onset (p = 0.611) and female sex predominance (p = 0.072) were similar in the 2 groups. The most common syndromes at sampling in both AQP4+NMOSD and DS-NMOSD were myelitis (56% vs 38.5%) and optic neuritis (34.6% vs 32%), with no statistical differences (p = 0.716). Median EDSS at sampling was 3.2 (interquartile range [IQR] 2-7.7) in the AQP4+NMOSD group and 4 (IQR [3-6]) in the DS-NMOSD group (p = 0.974). Serum GFAP, tau, and UCH-L1 levels were higher in patients with AQP4+NMOSD compared with those with DS-NMOSD (median 308.3 vs 103.4 pg/mL p = 0.001; median 1.2 vs 0.5 pg/mL, p = 0.001; and median 61.4 vs 35 pg/mL, p = 0.006, respectively). The ROC curve analysis showed that GFAP, tau, and UCH-L1, but not NfL, values were able to discriminate between AQP4+ and DS-NMOSD (area under the curve (AUC) tau: 0.782, p = 0.001, AUC GFAP: 0.762, p = 0.001, AUC UCH-L1: 0.723, p = 0.006). NfL levels were associated with EDSS at nadir only in patients with AQP4+NMOSD. Serum GFAP, tau, and UCH-L1 levels discriminate between AQP4+NMOSD and DS-NMOSD. The different biomarker profile of AQP4+NMOSD vs DS-NMOSD suggests heterogeneity of diseases within the latter category and provides useful data to improve our understanding of this disease.