DataSheet1_Autoregressive Modeling and Prediction of the Activity of Antihypertensive Peptides.zip

Naturally derived bioactive peptides with antihypertensive activities serve as promising alternatives to pharmaceutical drugs. There are few relevant reports on the mapping relationship between the EC50 value of antihypertensive peptide activity (AHTPA-EC50) and its corresponding amino acid sequence (AAS) at present. In this paper, we have constructed two group series based on sorting natural logarithm of AHTPA-EC50 or sorting its corresponding AAS encoding number. One group possesses two series, and we find that there must be a random number series in any group series. The random number series manifests fractal characteristics, and the constructed series of sorting natural logarithm of AHTPA-EC50 shows good autocorrelation characteristics. Therefore, two non-linear autoregressive models with exogenous input (NARXs) were established to describe the two series. A prediction method is further designed for AHTPA-EC50 prediction based on the proposed model. Two dynamic neural networks for NARXs (NARXNNs) are designed to verify the two series characteristics. Dipeptides and tripeptides are used to verify the proposed prediction method. The results show that the mean square error (MSE) of prediction is about 0.5589 for AHTPA-EC50 prediction when the classification of AAS is correct. The proposed method provides a solution for AHTPA-EC50 prediction.</p

Table1_Autoregressive Modeling and Prediction of the Activity of Antihypertensive Peptides.XLS

Naturally derived bioactive peptides with antihypertensive activities serve as promising alternatives to pharmaceutical drugs. There are few relevant reports on the mapping relationship between the EC50 value of antihypertensive peptide activity (AHTPA-EC50) and its corresponding amino acid sequence (AAS) at present. In this paper, we have constructed two group series based on sorting natural logarithm of AHTPA-EC50 or sorting its corresponding AAS encoding number. One group possesses two series, and we find that there must be a random number series in any group series. The random number series manifests fractal characteristics, and the constructed series of sorting natural logarithm of AHTPA-EC50 shows good autocorrelation characteristics. Therefore, two non-linear autoregressive models with exogenous input (NARXs) were established to describe the two series. A prediction method is further designed for AHTPA-EC50 prediction based on the proposed model. Two dynamic neural networks for NARXs (NARXNNs) are designed to verify the two series characteristics. Dipeptides and tripeptides are used to verify the proposed prediction method. The results show that the mean square error (MSE) of prediction is about 0.5589 for AHTPA-EC50 prediction when the classification of AAS is correct. The proposed method provides a solution for AHTPA-EC50 prediction.</p

X-ray tomography of extended objects: a comparison of data acquisition approaches

The penetration power of x-rays allows one to image large objects. For example, centimeter-sized specimens can be imaged with micron-level resolution using synchrotron sources. In this case, however, the limited beam diameter and detector size preclude the acquisition of the full sample in a single take, necessitating strategies for combining data from multiple regions. Object stitching involves the combination of local tomography data from overlapping regions, while projection stitching involves the collection of projections at multiple offset positions from the rotation axis followed by data merging and reconstruction. We compare these two approaches in terms of radiation dose applied to the specimen, and reconstructed image quality. Object stitching involves an easier data alignment problem, and immediate viewing of subregions before the entire dataset has been acquired. Projection stitching is more dose-efficient, and avoids certain artifacts of local tomography; however, it also involves a more difficult data assembly and alignment procedure, in that it is more sensitive to accumulative registration error

DataSheet_1_18F-FDG PET/CT radiomics nomogram for predicting occult lymph node metastasis of non-small cell lung cancer.docx

PurposeTo investigate the ability of a PET/CT-based radiomics nomogram to predict occult lymph node metastasis in patients with clinical stage N0 non-small cell lung cancer (NSCLC).Materials and methodsThis retrospective study included 228 patients with surgically confirmed NSCLC (training set, 159 patients; testing set, 69 patients). ITKsnap3.8.0 was used for image(CT and PET images) segmentation, AK version 3.2.0 was used for radiomics feature extraction, and Python3.7.0 was used for radiomics feature screening. A radiomics model for predicting occult lymph node metastasis was established using a logistic regression algorithm. A nomogram was constructed by combining radiomics scores with selected clinical predictors. Receiver operating characteristic (ROC) curves were used to verify the performance of the radiomics model and nomogram in the training and testing sets.ResultsThe radiomics nomogram comprising six selected features achieved good prediction efficiency, including radiomics characteristics and tumor location information (central or peripheral), which demonstrated good calibration and discrimination ability in the training (area under the ROC curve [AUC] = 0.884, 95% confidence interval [CI]: 0.826-0.941) and testing (AUC = 0.881, 95% CI: 0.8031-0.959) sets. Clinical decision curves demonstrated that the nomogram was clinically useful.ConclusionThe PET/CT-based radiomics nomogram is a noninvasive tool for predicting occult lymph node metastasis in NSCLC.</p

Three dimensions, two microscopes, one code: automatic differentiation for x-ray nanotomography beyond the depth of focus limit

Conventional tomographic reconstruction algorithms assume that one has obtained pure projection images, involving no within-specimen diffraction effects nor multiple scattering. Advances in x-ray nanotomography are leading towards the violation of these assumptions, by combining the high penetration power of x-rays which enables thick specimens to be imaged, with improved spatial resolution which decreases the depth of focus of the imaging system. We describe a reconstruction method where multiple scattering and diffraction effects in thick samples are modeled by multislice propagation, and the 3D object function is retrieved through iterative optimization. We show that the same proposed method works for both full-field microscopy, and for coherent scanning techniques like ptychography. Our implementation utilizes the optimization toolbox and the automatic differentiation capability of the open-source deep learning package TensorFlow, which demonstrates a much straightforward way to solve optimization problems in computational imaging, and endows our program great flexibility and portability

Characterizations and the Mechanism Underlying Osteogenic Activity of Peptides from Enzymatic Hydrolysates of <i>Stichopus japonicus</i>

Sea cucumber (Stichopus japonicus) is a kind of fishery product with high nutritional value. It exhibits a wide range of biological activity and has potential application in the food, pharmaceutical, and biomedical industries. However, there are no reports available on the effects of S. japonicus peptides (SJP) on bone mineral density regulations. The purpose of this work was to analyze the composition and osteogenic activity of SJP and explore its underlying mechanism. The results showed that SJP stimulated cell proliferation, differentiation, and mineralization in a dose-dependent manner. In addition, SJP could promote the proliferation of MC3T3-E1 cells by altering the cell cycle progression and regulating the expression of Cyclins. Besides, SJP activated the WNT/β-catenin pathway and increased the nuclear level of the active form β-catenin. Furthermore, SJP also induced the expression of bone morphogenetic protein (BMP-2) and increase the phosphorylation levels of p38, JNK, and ERK, suggesting that the osteogenic activity of SJP may be achieved through the activation of WNT/β-catenin and BMP/MAPK signal pathways. In vivo, SJP significantly inhibited the serum levels of RANKL, ALP, and TRAP, whereas it increased the levels of osteocalcin and osteoprotegerin in OVX-mice. These results indicate that SJP may have the potential to stimulate bone formation and regeneration, and may be used as a functional food or nutritional supplement to prevent osteoporosis

pH-Controllable Water Permeation through a Nanostructured Copper Mesh Film

Water permeation is an important issue in both fundamental research and industrial applications. In this work, we report a novel strategy to realize the controllable water permeation on the mixed thiol (containing both alkyl and carboxylic acid groups) modified nanostructured copper mesh films. For acidic and neutral water, the film is superhydrophobic, and the water cannot permeate the film because of the large negative capillary effect resulting from the nanostructures. For basic water, the film shows superhydrophilic property, and thus the water can permeate the film easily. The permeation process of water can be controlled just by simply altering the water pH. A detailed investigation indicates that nanostructures on the substrate and the appropriate size of the microscale mesh pores can enhance not only the static wettability but also the dynamic properties. The excellent controllability of water permeation is ascribed to the combined effect of the chemical variation of the carboxylic acid group and the microstructures on the substrate. This work may provide interesting insight into the new applications that are relevant to the surface wettability, such as filtration, microfluidic device, and some separation systems

Synergistic Antimicrobial Hybrid Bio-Surface Formed by Self-Assembled BSA Nanoarchitectures with Chitosan Oligosaccharide

Innovation in green, convenient, and sustainable antimicrobial packaging materials for food is an inevitable trend to address global food waste challenges caused by microbial contamination. In this study, we developed a biogenic, hydrophobic, and antimicrobial protein network coating for food packaging. Experimental results show that disulfide bond breakage can induce the self-assembly of bovine albumin (BSA) into protein networks driven by hydrophobic interactions, and chitosan oligosaccharide (COS) with antimicrobial activity can be stably bound in this network by electrostatic interactions. The inherent antimicrobial activity of COS and the numerous hydrophobic regions on the surface of the BSA-network give the BSA@COS-network significant in vitro antimicrobial ability. More importantly, the BSA@COS-network coating can prolong the onset of spoilage of strawberries in various packaging materials by nearly 3-fold in storage. This study shows how surface functionalization via protein self-assembly is integrated with the biological functioning of natural antibacterial activity for advanced food packaging applications

<i>Crassostrea gigas</i>-Based Bioactive Peptide Protected Thrombin-Treated Endothelial Cells against Thrombosis and Cell Barrier Dysfunction

The activation of thrombin-treated endothelial cells resulted in disruption of the vascular tissues. A novel oyster-derived bioactive dodecapeptide (IEELEELEAER, P-2-CG) was reported to protect the human umbilical vein endothelial cells and their barrier function via the decrease of VE-cadherin disruption and the restoration of the F-actin arrangement. The promotion of the extrinsic pathway in this case triggers the release of tissue factors that occurs on the surface of the endothelial cells, thus changing the antithrombotic to prothrombotic. P-2-CG induced accordingly a prolongation of plasma clotting time and thrombin generation time, following the alteration of the antithrombotic phenotype. Furthermore, the antithrombotic activity of P-2-CG was also supported by the reduction of FXa and the inhibition of other factors release, for instance, inflammation factors, ROS, etc. In addition to its antithrombogenic role, P-2-CG displayed anti-inflammatory and antioxidant properties via the mitogen-activated protein kinase cascades and central signaling pathways as shown in an in vitro model of endothelial dysfunction

<i>Crassostrea gigas</i>-Based Bioactive Peptide Protected Thrombin-Treated Endothelial Cells against Thrombosis and Cell Barrier Dysfunction

The activation of thrombin-treated endothelial cells resulted in disruption of the vascular tissues. A novel oyster-derived bioactive dodecapeptide (IEELEELEAER, P-2-CG) was reported to protect the human umbilical vein endothelial cells and their barrier function via the decrease of VE-cadherin disruption and the restoration of the F-actin arrangement. The promotion of the extrinsic pathway in this case triggers the release of tissue factors that occurs on the surface of the endothelial cells, thus changing the antithrombotic to prothrombotic. P-2-CG induced accordingly a prolongation of plasma clotting time and thrombin generation time, following the alteration of the antithrombotic phenotype. Furthermore, the antithrombotic activity of P-2-CG was also supported by the reduction of FXa and the inhibition of other factors release, for instance, inflammation factors, ROS, etc. In addition to its antithrombogenic role, P-2-CG displayed anti-inflammatory and antioxidant properties via the mitogen-activated protein kinase cascades and central signaling pathways as shown in an in vitro model of endothelial dysfunction