Computational Modeling of the C-Terminal Glycan of Type IV Pilin

Type IV pili are extracellular, filamentous, adhesive appendages that are assembled from a protein monomer called pilin. Type IV pili provide several properties to the bacterium, including twitching motility [1], DNA uptake [2], host-cell adhesion [3], and biofilm formation [4]. Besides these properties, type IV pili are also considered as the main virulence factor of bacterial pathogens. It has been shown that the C-terminal glycosylation of pilin, the pilus monomer, is an important source of bacteria virulence [5]. To discover how glycans influence the conformation and virulence of the Type IV pilin, I used the Rosetta software suite to model the C-terminal glycans along with the terminal protein residues of two types of Type IV major pilins, PilA ACICU and PilA M2, and analyzed the obtained structures from the perspectives of structures, root-mean-square deviations, hydrogen bonds, energies and surface areas. The results show that PilA ACICU has a tendency to be more flexible while PilA M2 is more constrained

Structural diversity in the type IV pili of multidrug-resistant Acinetobacter

Acinetobacter baumannii is a Gram-negative coccobacillus found primarily in hospital settings that has recently emerged as a source of hospital-acquired infections. A. baumannii expresses a variety of virulence factors, including type IV pili, bacterial extracellular appendages often essential for attachment to host cells. Here, we report the high resolution structures of the major pilin subunit, PilA, from three Acinetobacter strains, demonstrating thatA. baumannii subsets produce morphologically distinct type IV pilin glycoproteins. We examine the consequences of this heterogeneity for protein folding and assembly as well as host-cell adhesion by Acinetobacter. Comparisons of genomic and structural data with pilin proteins from other species of soil gammaproteobacteria suggest that these structural differences stem from evolutionary pressure that has resulted in three distinct classes of type IVa pilins, each found in multiple species

AhNRAMP1 Enhances Manganese and Zinc Uptake in Plants

Manganese (Mn) and zinc (Zn) play essential roles in plants. Members of the natural resistance-associated macrophage protein (NRAMP) family transport divalent metal ions. In this research, the function of peanut (Arachis hypogaea L.) AhNRAMP1 in transporting Mn and Zn, as well as its potential for iron(Fe) and Zn biofortification was examined. AhNRAMP1 transcription was strongly induced by Mn- or Zn-deficiency in roots and stems of peanut. Yeast complementation assays suggested that AhNRAMP1 encoded a functional Mn and Zn transporter. Exogenous expression of AhNRAMP1 in tobacco and rice enhanced Mn or Zn concentrations, improving tolerance to Mn or Zn deficiency. With higher Mn concentration, transgenic plants exhibited inhibited growth under Mn excess condition; similar results were obtained under excessive Zn treatment. AhNRAMP1 expression increased biomass in transgenic tobacco and rice, as well as yield in transgenic rice grown on calcareous soil. Compared with non-transformed (NT) plants, Fe and Zn concentrations were elevated whereas concentrations of Mn, copper (Cu), and cadmium (Cd) were not enhanced. These results revealed that AhNRAMP1 contributes to Mn and Zn transport in plants and may be a candidate gene for Fe and Zn biofortification

Mating Goals Moderate Power’s Effect on Conspicuous Consumption Among Women

This study aimed to use evolutionary psychology to explain conspicuous consumption’s relationship with mating goals among women. We used experiments to show that power moderates conspicuous consumption’s relationship with mating goals among women through an underlying relationship with women’s social comparison tendencies. In Study 1, the participants read a passage describing a young woman wearing a coat made by a conspicuous brand (vs. an ordinary brand) who aimed to attract a desired man (vs. aiming to guard against potential competitors’ attempts to disrupt her established intimate relationship). Participants in the conspicuous-brand condition were more confident that the young woman would succeed in mate attraction and guarding than participants in the ordinary-brand condition, suggesting the participants believed the conspicuous brands facilitated mate attraction and mate guarding more than ordinary brands. Study 2 manipulated the participants’ power states and mating goals and measured participants’ social comparison tendencies and conspicuous consumption index values. In the mate-guarding condition, high-power participants showed more inclination toward conspicuous consumption than low-power participants. In the mate-attraction condition, low-power participants showed a greater inclination toward conspicuous consumption than did high-power participants. Comparison orientation also mediated power’s effect on conspicuous consumption inclination. The evolutionary psychological basis for the above findings is discussed, and suggestions are offered regarding product marketing

Behavior monitoring model of kitchen staff based on YOLOv5l and DeepSort techniques

Although the monitoring system has been widely used, the actual monitoring task still needs more manpower to complete. This paper takes yolov5l model and deep sort algorithm as the basic framework to identify and track the staff in kitchen environment. We apply a relation construction with detected items and people, then label the relation corresponding to behaviors violate the regulations of kitchen, such as the staff did not wear mask or hat. We train our model and the experimental results show that the model can correctly identify the inappropriate behaviors of staff. The model achieves the time-constrained accuracy of 95.32% in identifying whether the staff wear a hat or not, and the time-constrained accuracy of 96.32% in identifying whether the staff wear mask correctly. The result shows that the proposed model could fulfil monitoring task in this kitchen environment

Diagnostic value of parameters derived from planar MUGA for detecting HFpEF in coronary artery disease patients

Abstract Background In recent years, heart failure with preserved ejection fraction (HFpEF) has received increasing clinical attention. To investigate the diagnostic value of diastolic function parameters derived from planar gated blood-pool imaging (MUGA) for detecting HFpEF in coronary atherosclerotic heart disease (coronary artery disease, CAD) patients. Methods Ninety-seven CAD patients with left ventricular ejection fraction ≥ 50% were included in the study. Based on the left ventricular end-diastolic pressure (LVEDP), the patients were divided into the HFpEF group (LVEDP ≥ 16 mmHg, 47 cases) and the normal LV diastolic function group (LVEDP < 16 mmHg, 50 cases). Diastolic function parameters obtained by planar MUGA include peak filling rate (PFR), filling fraction during the first third of diastole (1/3FF), filling rate during the first third of diastole (1/3FR), mean filling rate during diastole (MFR), and peak filling time (TPF). Echocardiographic parameters include left atrial volume index (LAVI), peak tricuspid regurgitation velocity (peak TR velocity), transmitral diastolic early peak inflow velocity (E), average early diastolic velocities of mitral annulars (average e′), average E/e′ ratio. The diastolic function parameters obtained by planar MUGA were compared with those obtained by echocardiography to explore the clinical value of planar MUGA for detecting HFpEF. Results The Receiver-operating characteristic curve analysis of diastolic function parameters obtained from planar MUGA and echocardiography to detect HFpEF showed that: among the parameters examined by planar MUGA, the area under the curve (AUC) of PFR, 1/3FF, 1/3FR, MFR and TPF were 0.827, 0.662, 0.653, 0.663 and 0.809, respectively. Among the echocardiographic parameters, the AUCs for average e′, average E/e′ ratio, peak TR velocity, and LAVI values were 0.747, 0.706, 0.735, and 0.633. The combination of PFR and TPF showed an AUC of 0.856. PFR combined with TPF value demonstrated better predictive value than average e′ (Z = 2.020, P = 0.043). Conclusion Diastolic function parameters obtained by planar MUGA can be used to diagnose HFpEF in CAD patients. PFR combined with TPF was superior to the parameters obtained by echocardiography and showed good sensitivity and predictive power for detecting HFpEF

DeepNitro: Prediction of Protein Nitration and Nitrosylation Sites by Deep Learning

Protein nitration and nitrosylation are essential post-translational modifications (PTMs) involved in many fundamental cellular processes. Recent studies have revealed that excessive levels of nitration and nitrosylation in some critical proteins are linked to numerous chronic diseases. Therefore, the identification of substrates that undergo such modifications in a site-specific manner is an important research topic in the community and will provide candidates for targeted therapy. In this study, we aimed to develop a computational tool for predicting nitration and nitrosylation sites in proteins. We first constructed four types of encoding features, including positional amino acid distributions, sequence contextual dependencies, physicochemical properties, and position-specific scoring features, to represent the modified residues. Based on these encoding features, we established a predictor called DeepNitro using deep learning methods for predicting protein nitration and nitrosylation. Using n-fold cross-validation, our evaluation shows great AUC values for DeepNitro, 0.65 for tyrosine nitration, 0.80 for tryptophan nitration, and 0.70 for cysteine nitrosylation, respectively, demonstrating the robustness and reliability of our tool. Also, when tested in the independent dataset, DeepNitro is substantially superior to other similar tools with a 7%−42% improvement in the prediction performance. Taken together, the application of deep learning method and novel encoding schemes, especially the position-specific scoring feature, greatly improves the accuracy of nitration and nitrosylation site prediction and may facilitate the prediction of other PTM sites. DeepNitro is implemented in JAVA and PHP and is freely available for academic research at http://deepnitro.renlab.org. Keywords: Protein nitration and nitrosylation, Deep learning, Web service, Functional site prediction, Feature extractio

Molecular Regulation of Catalpol and Acteoside Accumulation in Radial Striation and non-Radial Striation of <i>Rehmannia glutinosa</i> Tuberous Root

Rehmannia glutinosa L., a perennial plant of Scrophulariaceae, is one of the most commonly used herbs in traditional Chinese medicine (TCM) that have been widely cultivated in China. However, to date, the biosynthetic pathway of its two quality-control components, catalpol and acteoside, are only partially elucidated and the mechanism for their tissue-specific accumulation remains unknown. To facilitate the basic understanding of the key genes and transcriptional regulators involved in the biosynthesis of catalpol and acteoside, transcriptome sequencing of radial striation (RS) and non-radial striation (nRS) from four R. glutinosa cultivars was performed. A total of 715,158,202 (~107.27 Gb) high quality reads obtained using paired-end Illumina sequencing were de novo assembled into 150,405 transcripts. Functional annotation with multiple public databases identified 155 and 223 unigenes involved in catalpol and acteoside biosynthesis, together with 325 UGTs, and important transcription factor (TF) families. Comparative analysis of the transcriptomes identified 362 unigenes, found to be differentially expressed in all RS vs. nRS comparisons, with 143 upregulated unigenes, including those encoding enzymes of the catalpol and acteoside biosynthetic pathway, such as geranyl diphosphate synthase (RgGPPS), geraniol 8-hydroxylase (RgG10H), and phenylalanine ammonia-lyase (RgPAL). Other differentially expressed unigenes predicted to be related to catalpol and acteoside biosynthesis fall into UDP-dependent glycosyltransferases (UGTs), as well as transcription factors. In addition, 16 differentially expressed genes were selectively confirmed by real-time PCR. In conclusion, a large unigene dataset of R. glutinosa generated in the current study will serve as a resource for the identification of potential candidate genes for investigation of the tuberous root development and biosynthesis of active components