Effects of positively charged arginine residues on membrane pore forming activity of Rev–NIS peptide in bacterial cells

AbstractHere, we investigated antibacterial effects of Rev–NIS and suggested the role of positively charged amino acids on membrane pore forming activity of the peptide in bacterial cells, by synthesizing two analogs, Anal R and Anal S. Based on the amphipathic property of Rev–NIS, Anal R and Anal S were designed by substituting E1 and L3 to R and L3 to S, respectively. The circular dichroism (CD) spectroscopy showed that Anal R and Anal S have the same conformation of Rev–NIS, with a significant fraction of helical structure. In succession, the antibacterial susceptibility testing showed that Rev–NIS and its analogs possessed significant activities (Anal R>Rev–NIS>Anal S), without hemolytic effects, against bacterial pathogens including antibiotics-resistant strains. Moreover, the membrane studies, 3,3′-dipropylthiadicarbocyanine iodide (diSC35) staining and FITC-dextran (FD) leakage assay demonstrated that the analogs as well as Rev–NIS acted on the bacterial membranes and potently made pores, with the hydrodynamic radius between 1.4nm and 2.3nm. Especially, Anal R made larger pores than other peptides, with the radius between 2.3nm and 3.3nm. These results also corresponded to the result of antibacterial susceptibility testing. In summary, this study indicates that the two arginine residues are more influential than the hydrophobicity or the helicity, regarding the molecular activity of the peptide, and finally suggests that Anal R peptide may be applied to novel antibacterial agents

A Unified Masked Autoencoder with Patchified Skeletons for Motion Synthesis

The synthesis of human motion has traditionally been addressed through task-dependent models that focus on specific challenges, such as predicting future motions or filling in intermediate poses conditioned on known key-poses. In this paper, we present a novel task-independent model called UNIMASK-M, which can effectively address these challenges using a unified architecture. Our model obtains comparable or better performance than the state-of-the-art in each field. Inspired by Vision Transformers (ViTs), our UNIMASK-M model decomposes a human pose into body parts to leverage the spatio-temporal relationships existing in human motion. Moreover, we reformulate various pose-conditioned motion synthesis tasks as a reconstruction problem with different masking patterns given as input. By explicitly informing our model about the masked joints, our UNIMASK-M becomes more robust to occlusions. Experimental results show that our model successfully forecasts human motion on the Human3.6M dataset. Moreover, it achieves state-of-the-art results in motion inbetweening on the LaFAN1 dataset, particularly in long transition periods. More information can be found on the project website https://sites.google.com/view/estevevallsmascaro/publications/unimask-m

Antifungal effect and pore-forming action of lactoferricin B like peptide derived from centipede Scolopendra subspinipes mutilans

AbstractThe centipede Scolopendra subspinipes mutilans has been a medically important arthropod species by using it as a traditional medicine for the treatment of various diseases. In this study, we derived a novel lactoferricin B like peptide (LBLP) from the whole bodies of adult centipedes, S. s. mutilans, and investigated the antifungal effect of LBLP. LBLP exerted an antifungal and fungicidal activity without hemolysis. To investigate the antifungal mechanism of LBLP, a membrane study with propidium iodide was first conducted against Candida albicans. The result showed that LBLP caused fungal membrane permeabilization. The assays of the three dimensional flow cytometric contour plot and membrane potential further showed cell shrinkage and membrane depolarization by the membrane damage. Finally, we confirmed the membrane-active mechanism of LBLP by synthesizing model membranes, calcein and FITC-dextran loaded large unilamellar vesicles. These results showed that the antifungal effect of LBLP on membrane was due to the formation of pores with radii between 0.74nm and 1.4nm. In conclusion, this study suggests that LBLP exerts a potent antifungal activity by pore formation in the membrane, eventually leading to fungal cell death

Robust Human Motion Forecasting using Transformer-based Model

Comprehending human motion is a fundamental challenge for developing Human-Robot Collaborative applications. Computer vision researchers have addressed this field by only focusing on reducing error in predictions, but not taking into account the requirements to facilitate its implementation in robots. In this paper, we propose a new model based on Transformer that simultaneously deals with the real time 3D human motion forecasting in the short and long term. Our 2-Channel Transformer (2CH-TR) is able to efficiently exploit the spatio-temporal information of a shortly observed sequence (400ms) and generates a competitive accuracy against the current state-of-the-art. 2CH-TR stands out for the efficient performance of the Transformer, being lighter and faster than its competitors. In addition, our model is tested in conditions where the human motion is severely occluded, demonstrating its robustness in reconstructing and predicting 3D human motion in a highly noisy environment. Our experiment results show that the proposed 2CH-TR outperforms the ST-Transformer, which is another state-of-the-art model based on the Transformer, in terms of reconstruction and prediction under the same conditions of input prefix. Our model reduces in 8.89% the mean squared error of ST-Transformer in short-term prediction, and 2.57% in long-term prediction in Human3.6M dataset with 400ms input prefix.Comment: This paper has been already accepted to the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022

Human-Object Interaction Prediction in Videos through Gaze Following

Understanding the human-object interactions (HOIs) from a video is essential to fully comprehend a visual scene. This line of research has been addressed by detecting HOIs from images and lately from videos. However, the video-based HOI anticipation task in the third-person view remains understudied. In this paper, we design a framework to detect current HOIs and anticipate future HOIs in videos. We propose to leverage human gaze information since people often fixate on an object before interacting with it. These gaze features together with the scene contexts and the visual appearances of human-object pairs are fused through a spatio-temporal transformer. To evaluate the model in the HOI anticipation task in a multi-person scenario, we propose a set of person-wise multi-label metrics. Our model is trained and validated on the VidHOI dataset, which contains videos capturing daily life and is currently the largest video HOI dataset. Experimental results in the HOI detection task show that our approach improves the baseline by a great margin of 36.3% relatively. Moreover, we conduct an extensive ablation study to demonstrate the effectiveness of our modifications and extensions to the spatio-temporal transformer. Our code is publicly available on https://github.com/nizhf/hoi-prediction-gaze-transformer.Comment: Accepted by CVIU https://doi.org/10.1016/j.cviu.2023.10374

Expression, Immobilization and Enzymatic Properties of Glutamate Decarboxylase Fused to a Cellulose-Binding Domain

Escherichia coli-derived glutamate decarboxylase (GAD), an enzyme that catalyzes the conversion of glutamic acid to gamma-aminobutyric acid (GABA), was fused to the cellulose-binding domain (CBD) and a linker of Trichoderma harzianum endoglucanase II. To prevent proteolysis of the fusion protein, the native linker was replaced with a S3N10 peptide known to be completely resistant to E. coli endopeptidase. The CBD-GAD expressed in E. coli was successfully immobilized on Avicel, a crystalline cellulose, with binding capacity of 33 ± 2 nmolCBD-GAD/gAvicel and the immobilized enzymes retained 60% of their initial activities after 10 uses. The results of this report provide a feasible alternative to produce GABA using immobilized GAD through fusion to CBD

The antifungal activity and membrane-disruptive action of dioscin extracted from Dioscorea nipponica

AbstractDioscin is a kind of steroidal saponin isolated from the root bark of wild yam Dioscorea nipponica. We investigated the antifungal effect of dioscin against different fungal strains and its antifungal mechanism(s) in Candida albicans cells. Using the propidium iodide assay and calcein-leakage measurement, we confirmed that dioscin caused fungal membrane damage. Furthermore, we evaluated the ability of dioscin to disrupt the plasma membrane potential, using 3,3′-dipropylthiadicarbocyanine iodide [DiSC3(5)] and bis-(1,3-dibarbituric acid)-trimethine oxanol [DiBAC4(3)]. Cells stained with the dyes had a significant increase in fluorescent intensity after exposure to dioscin, indicating that dioscin has an effect on the membrane potential. To visualize the effect of dioscin on the cell membrane, we synthesized rhodamine-labeled giant unilamellar vesicles (GUVs) mimicking the outer leaflet of the plasma membrane of C. albicans. As seen in the result, the membrane disruptive action of dioscin caused morphological change and rhodamine leakage of the GUVs. In three-dimensional contour-plot analysis using flow cytometry, we observed a decrease in cell size, which is in agreement with our result from the GUV assay. These results suggest that dioscin exerts a considerable antifungal activity by disrupting the structure in membrane after invading into the fungal membrane, resulting in fungal cell death