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Escherichia coli O157:H7 is a recognized food-borne pathogen causing severe food poisoning at low doses. Bacteriophages (phages) are FDA-approved for use in food and are suggested as natural preservatives against specific pathogens. A novel phage must be identified and studied to develop a new natural preservative or antimicrobial agent against E. coli O157:H7. The phage SPEC13 displayed broad host range and was classified within the Ackermannviridae family based on its observed characteristics by a TEM and genome analysis. In 10 min, this phage achieves a remarkable 93% adsorption rate with the host. Its latency period then lasts about 20 min, after which it bursts, releasing an average of 139 ± 3 PFU/cell. It exhibited robustness within a pH range of 4 to 12, indicating resilience under diverse environmental circumstances. Furthermore, SPEC13 demonstrated stability at an ambient temperature up to 60 °C. A whole genome and phylogenetics analysis revealed that SPEC13 is a novel identified phage, lacking a lysogenic life cycle, antibiotic resistance genes, or genes associated with virulence, thereby presenting a promising biological agent for therapeutic application. Animal studies showed that SPEC13 effectively controlled the growth of harmful bacteria, resulting in a significant improvement in colon health, marked by reduced swelling (edema) and tissue damage (mucosal injury). The introduction of SPEC13 resulted in a substantial decrease in quantities of E. coli O157:H7, reducing the bacterial load to approximately 5 log CFU/g of feces. In conclusion, SPEC13 emerges as a promising inclusion in the array of phage therapy, offering a targeted and efficient approach for addressing bacterial infections. [ABSTRACT FROM AUTHOR]

Heart murmurs play a critical role in assessing the condition of the heart. Murmur quality reflects the subjective human perception of heart murmurs and is an important characteristic strongly linked to cardiovascular diseases (CVDs). This study aims to use deep neural networks to classify the patients' murmur quality (i.e., harsh and blowing) from phonocardiogram (PCG) signals. The phonocardiogram recordings with murmurs used for this task are from the CirCor DigiScope Phonocardiogram dataset, which provides the murmur quality labels. The recordings were segmented, and a dataset of 1266 segments with average lengths of 4.1 s from 164 patients' recordings was obtained. Each patient usually has multiple segments. A deep neural network model based on convolutional neural networks (CNNs) with channel attention and gated recurrent unit (GRU) networks was first used to extract features from the log-Mel spectrograms of segments. Then, the features of different segments from one patient were weighted by the proposed "Feature Attention" module based on the attention mechanism. The "Feature Attention" module contains a layer of global pooling and two fully connected layers. Through it, the different features can learn their weight, which can help the deep learning model distinguish the importance of different features of one patient. Finally, the detection results were produced. The cross-entropy loss function was used to train the model, and five-fold cross-validation was employed to evaluate the performance of the proposed methods. The accuracy of detecting the quality of patients' murmurs is 73.6%. The F1-scores (precision and recall) for the murmurs of harsh and blowing are 76.8% (73.0%, 83.0%) and 67.8% (76.0%, 63.3%), respectively. The proposed methods have been thoroughly evaluated and have the potential to assist physicians with the diagnosis of cardiovascular diseases as well as explore the relationship between murmur quality and cardiovascular diseases in depth. [ABSTRACT FROM AUTHOR]

Birds play a vital role in the study of ecosystems and biodiversity. Accurate bird identification helps monitor biodiversity, understand the functions of ecosystems, and develop effective conservation strategies. However, previous bird sound recognition methods often relied on single features and overlooked the spatial information associated with these features, leading to low accuracy. Recognizing this gap, the present study proposed a bird sound recognition method that employs multiple convolutional neural-based networks and a transformer encoder to provide a reliable solution for identifying and classifying birds based on their unique sounds. We manually extracted various acoustic features as model inputs, and feature fusion was applied to obtain the final set of feature vectors. Feature fusion combines the deep features extracted by various networks, resulting in a more comprehensive feature set, thereby improving recognition accuracy. The multiple integrated acoustic features, such as mel frequency cepstral coefficients (MFCC), chroma features (Chroma) and Tonnetz features, were encoded by a transformer encoder. The transformer encoder effectively extracted the positional relationships between bird sound features, resulting in enhanced recognition accuracy. The experimental results demonstrated the exceptional performance of our method with an accuracy of 97.99%, a recall of 96.14%, an F1 score of 96.88% and a precision of 97.97% on the Birdsdata dataset. Furthermore, our method achieved an accuracy of 93.18%, a recall of 92.43%, an F1 score of 93.14% and a precision of 93.25% on the Cornell Bird Challenge 2020 (CBC) dataset. [ABSTRACT FROM AUTHOR]

The self-assembly of lipid molecules in aqueous solution under shear flows was investigated using the dissipative particle dynamics simulation method. Three cases were considered: zero shear flow, weak shear flow and strong shear flow. Various self-assembled structures, such as double layers, perforated double layers, hierarchical discs, micelles, and vesicles, were observed. The self-assembly behavior was investigated in equilibrium by constructing phase diagrams based on chain lengths. Results showed the remarkable influence of chain length, shear flow and solution concentration on the self-assembly process. Furthermore, the self-assembly behavior of lipid molecules was analyzed using the system energy, particle number and shape factor during the dynamic processes, where the self-assembly pathways were observed and analyzed for the typical structures. The results enhance our understanding of biomacromolecule self-assembly in a solution and hold the potential for applications in biomedicine. [ABSTRACT FROM AUTHOR]

The interaction between macromolecular chains and phospholipid membranes in aqueous solution was investigated using dissipative particle dynamics simulations. Two cases were considered, one in which the macromolecular chains were pulled along parallel to the membrane surfaces and another in which they were pulled vertical to the membrane surfaces. Several parameters, including the radius of gyration, shape factor, particle number, and order parameter, were used to investigate the interaction mechanisms during the dynamics processes by adjusting the pulling force strength of the chains. In both cases, the results showed that the macromolecular chains undergo conformational transitions from a coiled to a rod-like structure. Furthermore, the simulations revealed that the membranes can be damaged and repaired during the dynamic processes. The role of the pulling forces and the adsorption interactions between the chains and membranes differed in the parallel and perpendicular pulling cases. These findings contribute to our understanding of the interaction mechanisms between macromolecules and membranes, and they may have potential applications in biology and medicine. [ABSTRACT FROM AUTHOR]

Inflammation of the fetal membranes is an indispensable event of parturition, with increasing prostaglandin E2 (PGE2) synthesis as one of the ultimate products that prime labor onset. In addition to PGE2, the fetal membranes also boast a large capacity for cortisol regeneration. It is intriguing how increased PGE2 synthesis is achieved in the presence of increasing amounts of classical anti-inflammatory glucocorticoids in the fetal membranes at parturition. 15(S)-hydroxyeicosatetraenoic acid (15(S)-HETE) synthesized by lipoxygenase 15/15B (ALOX15/15B) has been shown to enhance inflammation-induced PGE2 synthesis in amnion fibroblasts. Here, we examined whether glucocorticoids could induce ALOX15/15B expression and 15(S)-HETE production to promote PGE2 synthesis in amnion fibroblasts at parturition. We found that cortisol and 15(S)-HETE abundance increased parallelly in the amnion at parturition. Cortisol induced ALOX15/15B expression and 15(S)-HETE production paradoxically in amnion fibroblasts. Mechanism study revealed that this paradoxical induction was mediated by p300-mediated histone acetylation and interaction of glucocorticoid receptor with transcription factors CREB and STAT3. Conclusively, cortisol regenerated in the fetal membranes can paradoxically induce ALOX15/15B expression and 15(S)-HETE production in human amnion fibroblasts, which may further assist in the induction of PGE2 synthesis in the inflammatory responses of the fetal membranes for parturition. [ABSTRACT FROM AUTHOR]

In this study, we investigate the dynamic processes and mechanical properties of lipid nanoparticle mixtures in a melt via dissipation particle dynamic simulation. By investigating the distribution of nanoparticles in lamellar and hexagonal lipid matrices in equilibrium state and dynamic processes, we observe that the morphology of such composites depends not only on the geometric features of the lipid matrix but also on the concentration of nanoparticles. The dynamic processes are also demonstrated by calculating the average radius of gyration, which indicates the isotropic conformation of lipid molecules in the x–y plane and that the lipid chains are stretched in the z direction with the addition of nanoparticles. Meanwhile, we predict the mechanical properties of lipid–nanoparticle mixtures in lamellar structures by analyzing the interfacial tensions. Results show that the interfacial tension decreased with the increase in nanoparticle concentration. These results provide molecular-level information for the rational and a priori design of new lipid nanocomposites with ad hoc tailored properties. [ABSTRACT FROM AUTHOR]

Diastereoisomers of quinidine and quinine are used to treat arrhythmia and malaria, respectively. It has been reported that both drugs block the hERG (human ether-a-go-go-related gene) potassium channel which is essential for myocardium repolarization. Abnormality of repolarization increases risk of arrhythmia. The aim of our research is to study and compare the impacts of quinidine and quinine on hERG. Results show that both drugs block the hERG channel, with quinine 14-fold less potent than quinidine. In addition, they presented distinct impacts on channel dynamics. The results imply their stereospecific block effect on the hERG channel. However, F656C-hERG reversed this stereoselectivity. The mutation decreases affinity of the two drugs with hERG, and quinine was more potent than quinidine in F656C-hERG blockage. These data suggest that F656 residue contributes to the stereoselective pocket for quinidine and quinine. Further study demonstrates that both drugs do not change hERG protein levels. In rescue experiments, we found that they exert no reverse effect on pentamidine- or desipramine-induced hERG trafficking defect, although quinidine has been reported to rescue trafficking-deficient pore mutation hERG G601S based on the interaction with F656. Our research demonstrated stereoselective effects of quinidine and quinine on the hERG channel, and this is the first study to explore their reversal potency on drug-induced hERG deficiency. [ABSTRACT FROM AUTHOR]

To explore the influence of the decomposition of aquatic macrophytes on water quality in eutrophicated aquatic ecosystems and the interacting environmental factors that trigger nitrogen (N) and phosphorus (P) dynamics, a suburban pond with floating-leaved macrophytes (Pond A) as well as another nearby newly dug pond without any obvious aquatic macrophytes (Pond B) were studied. N and P levels together with a series of parameters relating to biomass, water and sediments were monitored during a period of 84 d that covered the entire decomposition process of plants. The results show that the decomposition of aquatic macrophytes can be divided into two phases, with the first phase having a faster decomposition rate and the second phase, a slower one. With the decomposition of biomass, the dissolved oxygen (DO), oxidation-reduction potential (ORP), and pondus hydrogenii (pH) of the water body increased, whereas the permanganate index (CODMn) decreased. Significantly higher levels of total phosphorus in both water and sediment (TPW and TPS) were detected in Pond A with macrophytes; TPW increased quickly during the first phase of biomass decomposition but decreased in the second phase, and TPS remained relatively stable during the first phase but increased slowly in the second phase. Total nitrogen in both water and sediment (TNW and TNS) was also significantly higher in Pond A but remained relatively stable. A structural equation model revealed that the decomposition of aquatic macrophytes, could, directly and indirectly, influence N and P cycles in an aquatic ecosystem through the regulation of pH and DO. Our study indicate that the decomposition of biomass exerted a greater influence on P than on N. Besides the direct release of P from decaying biomass, which caused a significant increase of P in water body, changes of DO and ORP and the subsequent redox state of the whole system during the process also indirectly affected the deposition and dissolution of P between sediment and water. P was the decisive factor that caused endogenous eutrophication in ponds containing aquatic macrophytes. [ABSTRACT FROM AUTHOR]

Simple Summary: LmPrx6 of the insulin signaling pathway is significantly associated with diapause induction in Locusta migratoria L. as per our pervious transcriptome data. In the current study, we first cloned and sequenced the gene and demonstrated its similarity to other Prxs using phylogenetic analyses. Later on, we knocked down Prx6 using RNAi and showed that phosphorylation of proteins associated with the insulin signaling pathway and responses to oxidative stress were altered. Knockdown of Prx6 also resulted in a reduced ability to enter diapause, and hence, we are of the opinion that this gene could serve as an effective target for RNAi-based control of L. migratoria L. The study has provided some helpful insights into the diversified roles of Prx6 in locusts and will be of interest to other insect pests for examining the relatively unexplored group of proteins as well. Peroxiredoxins (Prxs), which scavenge reactive oxygen species (ROS), are cysteine-dependent peroxide reductases that group into six structurally discernable classes: AhpC-Prx1, BCP-PrxQ, Prx5, Prx6, Tpx, and AhpE. A previous study showed that forkhead box protein O (FOXO) in the insulin signaling pathway (ISP) plays a vital role in regulating locust diapause by phosphorylation, which can be promoted by the high level of ROS. Furthermore, the analysis of transcriptome between diapause and non-diapause phenotypes showed that one of the Prxs, LmPrx6, which belongs to the Prx6 class, was involved. We presumed that LmPrx6 might play a critical role in diapause induction of Locusta migratoria and LmPrx6 may therefore provide a useful target of control methods based on RNA interference (RNAi). To verify our hypothesis, LmPrx6 was initially cloned from L. migratoria to make dsLmPrx6 and four important targets were tested, including protein-tyrosine phosphorylase 1B (LmPTP1B), insulin receptor (LmIR), RAC serine/threonine-protein kinase (LmAKT), and LmFOXO in ISP. When LmPrx6 was knocked down, the diapause rate was significantly reduced. The phosphorylation level of LmPTP1B significantly decreased while the phosphorylation levels of LmIR, LmAKT, and LmFOXO were significantly increased. Moreover, we identified the effect on two categories of genes downstream of LmFOXO, including stress tolerance and storage of energy reserves. Results showed that the mRNA levels of catalase and Mn superoxide dismutase (Mn-SOD), which enhanced stress tolerance, were significantly downregulated after silencing of LmPrx6. The mRNA levels of glycogen synthase and phosphoenolpyruvate carboxy kinase (PEPCK) that influence energy storage were also downregulated after knocking down of LmPrx6. The silencing of LmPrx6 indicates that this regulatory protein may probably be an ideal target for RNAi-based diapause control of L. migratoria. [ABSTRACT FROM AUTHOR]

This study describes the chemical constituents of Albiziae Cortex and their ability to ameliorate steatosis and promote proliferation and anti-oxidation in vitro. Together, five known lignan glycosides, (7S,8R)-erythro-syringylglycerol-β–O-4′-sinapyl ether 9-O-β-D-glucopyranoside (1), (+)-lyoniresinol-9′-O-gluco-side (2), (−)-lyoniresinol-9′-O-glucoside (3), picraquassioside C (4), and icariside E5 (5), were isolated from the Albiziae Cortex. Their structures were elucidated by extensive NMR and high-resolution mass spectrometry analysis and compared with reported data. Oil Red O staining results revealed that compounds 1, 2, and 3 attenuated lipid accumulation and lipid metabolic disorders in FFAs (oleate/palmitate, 2:1 ratio, 0.3 mM)-exposed HepG2 cells. The Cell Counting Kit 8 (CCK-8) assay results revealed that compounds 1 and 5 can significantly promote human umbilical vein endothelial cell (HUVEC) proliferation; meanwhile, these compounds did not exhibit significant cytotoxicity against HUVECs. In addition, 2′,7′-dichlorofluorescein diacetate (DCFH-DA) staining results revealed that high glucose (HG)-induced reactive oxygen species (ROS) production was abolished by compounds 1, 2, and 3. This is the first report of the isolation of lignan skeletons from the genus Albizzia julibrissin with the ability to ameliorate steatosis and promote proliferation and anti-oxidation activities. [ABSTRACT FROM AUTHOR]

Mesoporous TiO2 containing different potassium content was prepared from potassium titanate by mediating the pH value of the ion exchange, which was used as catalytic support to load NiMo for hydrodesulfurization of dibenzothiophene. The as-prepared samples were characterized by X-ray diffraction, N2 physical adsorption/desorption, temperature-programmed reduction, scanning electron microscope/energy dispersive X-ray mapping analysis, high resolution transmission electron microscopy, and pyridine-adsorbed Fourier transform infrared spectroscopy. The characterization results showed that NiO and MoO3 were well dispersed on mesoporous TiO2 with varying potassium content. A crystal NiMoO4 phase was formed on the TiO2 with relatively high potassium content, which could decrease the reduction temperature of oxidized active species. The evaluation results from the hydrodesulfurization displayed that as the potassium content of the catalyst increased, the dibenzothiophene conversion firstly increased and then slightly decreased when potassium content exceeded 6.41 wt %. By contrast, the direct desulfurization selectivity could continuously increase along with the potassium content of catalyst. Furthermore, the change in direct desulfurization selectivity of a TiO2-supported NiMo catalyst was independent of the reaction condition. The mesoporous TiO2-supported NiMo catalyst incorporated with potassium could have near both 100% of dibenzothiophene and 100% of direct desulfurization selectivity. According to the structure–performance relationship discussion, the incorporation of potassium species could benefit the formation of more sulfided active species on mesoporous TiO2. Moreover, excessive free potassium species may poison the active sites of the hydrogenation pathway. Both factors determined the characteristics of complete hydrodesulfurization of dibenzothiophene via a direct desulfurization pathway for potassium-incorporated mesoporous TiO2 supported NiMo catalysts. [ABSTRACT FROM AUTHOR]

Image encryption is one of the essential tasks in image security. In this paper, we propose a novel approach that integrates a hyperchaotic system, pixel-level Dynamic Filtering, DNA computing, and operations on 3D Latin Cubes, namely DFDLC, for image encryption. Specifically, the approach consists of five stages: (1) a newly proposed 5D hyperchaotic system with two positive Lyapunov exponents is applied to generate a pseudorandom sequence; (2) for each pixel in an image, a filtering operation with different templates called dynamic filtering is conducted to diffuse the image; (3) DNA encoding is applied to the diffused image and then the DNA-level image is transformed into several 3D DNA-level cubes; (4) Latin cube is operated on each DNA-level cube; and (5) all the DNA cubes are integrated and decoded to a 2D cipher image. Extensive experiments are conducted on public testing images, and the results show that the proposed DFDLC can achieve state-of-the-art results in terms of several evaluation criteria. [ABSTRACT FROM AUTHOR]