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UnaG is a new class of fluorescence protein in which an endogenous ligand, namely bilirubin (BLR), plays the role of chromophore. Upon photoexcitation, holoUnaG emits green light. A single mutation at residue 57 induces a decrease in the fluorescence quantum yield. To our knowledge, no atomic simulation at the atomic level has been carried out to date to explain this fluorescence decay in N57A and N57Q mutants. Herein molecular dynamics simulations were carried out on wild-type (WT) UnaG and both mutants to investigate the structural impact of the mutation on its global structure, on BLR and the absorption spectra. Our study reveals significant global changes upon mutation at the protein entrance (L3, H2, and, H3) governing a BLR modification. BLR in WT UnaG is rather rigid while when embedded into N57A or N57Q, dihedral angles between endo and exo vinyl moieties and between A and B rings at the entrance of UnaG are strongly modified along with the number of inter-/intramolecular interactions. The water molecules play an important role in the modification of the shape of the binding cavity. For the first time, we show that the structural modifications upon ligand mutations are tightly related to the key structural changes in the protein such as Loop3 (L3), β sheet 2 (B2), and β sheet 3 (B3) dynamics. The present work suggests that the quenching of the fluorescence properties of UnaG mutants is mainly a non-radiative process closely related to the BLR flexibility induced by global structural changes. [ABSTRACT FROM AUTHOR]

Background It's critical to identify COVID-19 patients with a higher death risk at early stage to give them better hospitalization or intensive care. However, thus far, none of the machine learning models has been shown to be successful in an independent cohort. We aim to develop a machine learning model which could accurately predict death risk of COVID-19 patients at an early stage in other independent cohorts. Methods We used a cohort containing 4711 patients whose clinical features associated with patient physiological conditions or lab test data associated with inflammation, hepatorenal function, cardiovascular function, and so on to identify key features. To do so, we first developed a novel data preprocessing approach to clean up clinical features and then developed an ensemble machine learning method to identify key features. Results Finally, we identified 14 key clinical features whose combination reached a good predictive performance of area under the receiver operating characteristic curve 0.907. Most importantly, we successfully validated these key features in a large independent cohort containing 15 790 patients. Conclusions Our study shows that 14 key features are robust and useful in predicting the risk of death in patients confirmed SARS-CoV-2 infection at an early stage, and potentially useful in clinical settings to help in making clinical decisions. [ABSTRACT FROM AUTHOR]

Background and Aim: Hepatocellular carcinoma (HCC), a primary liver malignancy, represents a continuous challenge to clinicians as it is a leading cause of death due to cancer widely. Early detection is the only hope to cure patients from this deadly disease or possibly increase life expectancy. Mouse models are most acceptable studies as they have ability to manipulate their genome and transcriptome to evaluate mechanistic changes. In addition, system biology can improvise the understanding of molecular mechanism of HCC and also can reveal the protein hub involved in every stage of HCC. Materials and Methods: Herein, diethylnitrosamine and thioacetamide (TAA) were used to develop stage-specific HCC in Wistar rats. Histopathological changes, biochemical parameters, and the oxidative stress were measured in hepatocytes. We have reanalyzed the microarray dataset to identify the complex signaling pathways involved in hepatocarcinogenesis induced by TAA. GSE45050 dataset was downloaded from Gene Expression Omnibus database, and the gene expression profile of nontumor, cirrhosis, and HCC was compared. Results: The study reveals stage-specific development of chronic HCC rat model and promising stage-specific targets (EHMT2, GMPS, and SPRY2) of HCC. Conclusions: EHMT2, GMPS, and SPRY found as high centrality nodes in protein-protein interaction studies using high-throughput microarray data which tend to be present in signaling pathways and co-occur in a biological state of HCC. These genes can be targeted to understand the possible pathology, molecular changes, and target strategy under cirrhosis and HCC condition. [ABSTRACT FROM AUTHOR]

Background: Dryopteris ramosa has numerous potentials uses in the treatment of different maladies as old traditional medication. The fronds of D. ramose are edible and orally administered for producing antibiotic effect. They are also used as astringent and febrifuge, and as a pesticide. Methods: Extraction of fronds of D. ramosa using solvents of increasing polarity, namely, ethyl acetate, methanol and water were tested for phytochemical (qualitative tests, GC-MS), antimicrobial (well method), antioxidant (DPPH), antifungal (tube dilution), cytotoxic activity (brine shrimps lethality assay) and LOX and COX inhibitory activities were performed using standard methods. Results: The phytochemical analysis of the crude methanolic extract revealed that the fronds are rich in flavonoids, alkaloids, saponins, tannins, glycosides and triterpenoids. The total flavonoid content of the ethyl acetate fraction was 46.28 μg QE/mg extract. The GC-MS analysis revealed nine major compounds that constituted the crude drug and potentially had a role in reported activities. The crude extract was the most active amongst all the fractions against the bacterial and fungal strains used such that it inhibited the growth of P. aeruginosa with a zone of 13 mm and a MIC value of 16 μg/ml as compared to the standard cefixime, which inhibited the zone by only 10 mm and a MIC value of 32 μg/ml. The highest antioxidant potential in DPPH assay was shown by the crude extract with 91.948% free radical scavenging activity. The bring shrimps lethality potential of the crude extract was the highest, with a LD50 value of 47.635 μg/ml. The ethyl acetate fraction inhibits 91.36% of alpha glucosidase enzyme at a concentration of 0.5 mg/ml. In case of acetylcholine esterase inhibition assay, the methanol fraction inhibits 58.26% of the enzyme activity. Similarly, for butyrylcholine esterase inhibition, the maximum inhibitory effect was seen in the methanol fraction, with a percentage inhibition of 47.32%. Conclusion: These test results support traditional medicinal uses of the plant. Dryopteris ramosa could be imperative for being used as a therapeutic agent and the medicinal importance of this plant should be further investigated. [ABSTRACT FROM AUTHOR]

This study investigated combined alkali and heat pretreatment of lignocellulosic biomass for fermentative bioethanol production. Prior to fermentation, alkali pretreatment of corn stalk (CS) was carried out in NaOH solution under varying concentration which was followed by incubation at 100 °C for 1 h. The slurry of alkali-pretreated CS was supplemented with media and incubated at 30 °C, 96 h and pH 5. The 2.0% alkali pretreatment was most effective. Further optimization studies with filtrate and 5% inoculum size produced 43.8 g/L bioethanol. Chemical analysis of CS shows 61.75 and 71.49% degradation of hemicellulose and lignin, respectively, under optimal conditions. Structural changes of CS biomass monitored via scanning electron microscope showed that pretreatment with NaOH induced porosity and surface area disruption when compared to the untreated samples. Pretreated CS showed higher crystallinity index as revealed by X-ray diffraction analysis. The results showed that alkali-pretreated CS can serve as a potential feed stock for bioethanol production to reduce dependency on fossil fuel. [ABSTRACT FROM AUTHOR]

Corn stalk (CS) is one of the most abundant agricultural residues containing high polysaccharides for low-cost bioethanol production. In this study, dilute acid along with intensified thermal pretreatment of CS and other parameters were optimized for higher yield of bioethanol. CS samples were pretreated using H2SO4 concentrations of 0.5, 1.0, 1.5, 2.0, and 2.5% at 100 °C for 1 h reaction time. Optimal conditions of 2% acid-pretreated CS, 5% (w/v) of Saccharomyces cerevisiae addition and 48 h fermentation produced highest yield of bioethanol: 32.53 (g/L) which was 1.24-fold increase. Hemicellulose degradation of 75.68% was recorded in the 2% acid-treated substrate. Scanning electron microscope (SEM) images revealed induced porosity and surface area disruption of CS in the treated samples. Crystallinity of the treated samples increased as shown by X-ray diffraction (XRD) analysis. Low concentrated H2SO4 coupled with thermal pretreatment could be a viable method of lignocellulosic biomass utilization for efficient bioethanol production. [ABSTRACT FROM AUTHOR]

• Analysed masonry walls under hydrodynamic and hydrostatic loads. • Correlated rise of water level against the wall to its damage during the flood. • Correlated submerged surface area of the wall to its slenderness ratio. • Element deletion technique used to simulate opening of micro-cracks in masonry wall under flash flood. • Water rise after the first impulsive hit can cause early collapse of the wall due to stiffness reduction. Damage surveys from past flash flood events show that the combined hydrodynamic impulsive loading and the subsequent hydrostatic loading due to rising water levels caused the failure of masonry walls/buildings. However, limited studies have been conducted to understand the responses of masonry walls to these loading states. To bridge this knowledge gap, an explicit 3D shell element based finite element modelling method that incorporates a homogenised anisotropic masonry material model was developed and applied to analyse the out-of-plane collapse behaviour of masonry walls under flash flooding conditions. The developed modelling method was validated with an available experimental study of masonry wall subjected to hydrostatic loading conditions. It was then extended to comprehend the behaviour of masonry walls under hydrodynamic impulsive water pressures. Results reveal that the effect of hydrodynamic impulsive loading generated by the first hit of the flash flood water is significant in reducing the stiffness of the masonry. This reduction in stiffness can result in an early collapse of the wall, even with a gradual rise of hydrostatic water level. This study has also evaluated the behaviour and damage patterns of masonry walls with two different slenderness ratios (single brick/24.5 and double brick/11.7) under flash flooding and prescribed the maximum percentage of surface area of inundation that the walls can resist. The importance of considering hydrodynamic impulsive loading in designing masonry buildings vulnerable to flash flooding and the capability of the modelling technique developed in this research for evaluating their vulnerability under these flooding scenarios are highlighted. [ABSTRACT FROM AUTHOR]

Conversely, tissue neutrophil association with LM scores in N-ERD patients suggests that neutrophils contribute to the severity of the polyp burden in N-ERD. Neutrophilic inflammation and epithelial barrier disruption in nasal polyps characterize non-steroidal anti-inflammatory drug exacerbated respiratory disease Neutrophil counts were higher in the nasal polyp tissues of N-ERD patients (8.5 cells per hpf (IQR 3-25) vs. 2.5 cells (IQR 2-5) in non-N-ERD ( I p i = .026, Figure 1B). [Extracted from the article]