Texts of Kolima dialect of Yukaghir

<p>Clinical chemistry data of monkeys fed on diets containing GM rice or non-GM rice.</p

Resilient Supply Chain Planning for the Perishable Products under Different Uncertainty

In this research, the perishable products’ closed-loop supply chain network design problem is assessed by considering the disruption in production and distribution capacity and taking into account the uncertainty in customer demand. The main contribution of this research is modeling perishable products’ supply chain optimization and providing intelligent solution methods. In this regard, a mixed-integer mathematical model is proposed. This mathematical model consists of three objective functions. The first objective function is related to profit maximization, the second objective function is to minimize delivery time, and the third objective function is to reduce lost business days. Moreover, non-dominated sorting genetic algorithm II (NSGAII) and Multi-Objective Evolutionary Algorithm (MOEA) have been applied to optimize the proposed model. The research results show that the proposed meta-heuristic algorithm can provide a complete set of Pareto solutions in a reasonable amount of time. Moreover, based on different criteria, MOEA provides the non-dominated solutions with a higher quality, while NSGAII presents the Pareto boundary with more solutions than MOEA.</p

Additional file 1: of Quantitative succinylome analysis in the liver of non-alcoholic fatty liver disease rat model

The summary of all the identified succinylation sites and corresponding proteins. (XLSX 71 kb

Iron-Adjustable Compressible Elastic Chitosan-Derived Carbon Aerogel with Wide-Range Linear Sensitivity and Super Sensing Performances for Wearable Piezoresistive Sensors

Ultra-light elastic carbon aerogels with high compressibility have broad application prospects in wearable devices. Especially, they are ideal materials for fabricating flexible piezoresistive sensors. In this paper, an ultra-light carbon aerogel was successfully fabricated using freeze-drying and carbonization of the solution containing chitosan (CS), polyimide (PI), and FeCl3·6H2O. Owing to the interplay interaction between CS and PI and the adjustment of the FeCl3 concentration, this carbon aerogel with compact, continuous, ordered, layered structure shows a wide range of excellent sensing properties (10.28 kPa–1 and 0–6 kPa), remarkable long-term stability (1000 cycles), and outstanding mechanical properties (withstand up to 95% compression strain and 1000 cycles compression under 50% strain without deformation). In addition, the carbon aerogel can be bent to detect different angular changes. These advantages mentioned above allow carbon aerogel to be wildly used to detect human movement and biological signals

Iron-Adjustable Compressible Elastic Chitosan-Derived Carbon Aerogel with Wide-Range Linear Sensitivity and Super Sensing Performances for Wearable Piezoresistive Sensors

Ultra-light elastic carbon aerogels with high compressibility have broad application prospects in wearable devices. Especially, they are ideal materials for fabricating flexible piezoresistive sensors. In this paper, an ultra-light carbon aerogel was successfully fabricated using freeze-drying and carbonization of the solution containing chitosan (CS), polyimide (PI), and FeCl3·6H2O. Owing to the interplay interaction between CS and PI and the adjustment of the FeCl3 concentration, this carbon aerogel with compact, continuous, ordered, layered structure shows a wide range of excellent sensing properties (10.28 kPa–1 and 0–6 kPa), remarkable long-term stability (1000 cycles), and outstanding mechanical properties (withstand up to 95% compression strain and 1000 cycles compression under 50% strain without deformation). In addition, the carbon aerogel can be bent to detect different angular changes. These advantages mentioned above allow carbon aerogel to be wildly used to detect human movement and biological signals

Iron-Adjustable Compressible Elastic Chitosan-Derived Carbon Aerogel with Wide-Range Linear Sensitivity and Super Sensing Performances for Wearable Piezoresistive Sensors

Ultra-light elastic carbon aerogels with high compressibility have broad application prospects in wearable devices. Especially, they are ideal materials for fabricating flexible piezoresistive sensors. In this paper, an ultra-light carbon aerogel was successfully fabricated using freeze-drying and carbonization of the solution containing chitosan (CS), polyimide (PI), and FeCl3·6H2O. Owing to the interplay interaction between CS and PI and the adjustment of the FeCl3 concentration, this carbon aerogel with compact, continuous, ordered, layered structure shows a wide range of excellent sensing properties (10.28 kPa–1 and 0–6 kPa), remarkable long-term stability (1000 cycles), and outstanding mechanical properties (withstand up to 95% compression strain and 1000 cycles compression under 50% strain without deformation). In addition, the carbon aerogel can be bent to detect different angular changes. These advantages mentioned above allow carbon aerogel to be wildly used to detect human movement and biological signals

Additional file 2: of Quantitative succinylome analysis in the liver of non-alcoholic fatty liver disease rat model

The detailed description of the experiment methods, including rat model establishment, mass spectrometric analysis procedures and parameters, bioinformatics analysis softwares, websites. (DOCX 18 kb

Table_2_Network Pharmacology–Based Prediction and Pharmacological Validation of Effects of Astragali Radix on Acetaminophen-Induced Liver Injury.XLS

Astragali Radix (AR) has been widely used in traditional Chinese medicine prescriptions for acute and chronic liver injury. However, little is known about the effects of AR on acetaminophen (APAP)-induced liver injury (ALI). In the current study, a network pharmacology–based approach was applied to characterize the action mechanism of AR on ALI. All compounds of AR were obtained from the corresponding databases, and active compounds were selected according to its oral bioavailability and drug-likeness index. The potential genes of AR were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM) and PubChem, whereas the potential genes related to ALI were obtained from Online databases (GeneCards and Online Mendelian Inheritance in Man) and Gene Expression Omnibus profiles. The enriched processes, pathways, and target genes of the diseases were analyzed by referring to the Search Tool for the Retrieval of Interacting Genes/Proteins database. A network constructed through Cytoscape software was used to identify the target proteins that connected the compounds in AR with the differential genes of ALI. Subsequently, the potential underlying action mechanisms of AR on ALI predicted by the network pharmacology analyses were experimentally validated in APAP-induced liver injury in mice and HL7702 cells incubated with APAP. The compound-target network included 181 targets, whereas the potential genes related to ALI were 4,621. A total of 49 AR–ALI crossover proteins, corresponding to 49 genes, were filtered into a protein–protein interaction network complex and designated as the potential targets of AR on ALI. Among the genes, the three highest-scoring genes, MYC, MAPK8, and CXCL8 were highly associated with apoptosis in ALI. Then in vitro and in vivo experiments confirmed that AR exhibited its prominent therapeutic effects on ALI mainly via regulating hepatocyte apoptosis related to inhibiting the expressions of MYC (c-Myc), MAPK8 (JNK1), and CXCL8 (IL-8). In conclusion, our study suggested that the combination of network pharmacology prediction with experimental validation might offer a useful tool to characterize the molecular mechanism of AR on ALI.</p

Table_1_Network Pharmacology–Based Prediction and Pharmacological Validation of Effects of Astragali Radix on Acetaminophen-Induced Liver Injury.DOCX

Astragali Radix (AR) has been widely used in traditional Chinese medicine prescriptions for acute and chronic liver injury. However, little is known about the effects of AR on acetaminophen (APAP)-induced liver injury (ALI). In the current study, a network pharmacology–based approach was applied to characterize the action mechanism of AR on ALI. All compounds of AR were obtained from the corresponding databases, and active compounds were selected according to its oral bioavailability and drug-likeness index. The potential genes of AR were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM) and PubChem, whereas the potential genes related to ALI were obtained from Online databases (GeneCards and Online Mendelian Inheritance in Man) and Gene Expression Omnibus profiles. The enriched processes, pathways, and target genes of the diseases were analyzed by referring to the Search Tool for the Retrieval of Interacting Genes/Proteins database. A network constructed through Cytoscape software was used to identify the target proteins that connected the compounds in AR with the differential genes of ALI. Subsequently, the potential underlying action mechanisms of AR on ALI predicted by the network pharmacology analyses were experimentally validated in APAP-induced liver injury in mice and HL7702 cells incubated with APAP. The compound-target network included 181 targets, whereas the potential genes related to ALI were 4,621. A total of 49 AR–ALI crossover proteins, corresponding to 49 genes, were filtered into a protein–protein interaction network complex and designated as the potential targets of AR on ALI. Among the genes, the three highest-scoring genes, MYC, MAPK8, and CXCL8 were highly associated with apoptosis in ALI. Then in vitro and in vivo experiments confirmed that AR exhibited its prominent therapeutic effects on ALI mainly via regulating hepatocyte apoptosis related to inhibiting the expressions of MYC (c-Myc), MAPK8 (JNK1), and CXCL8 (IL-8). In conclusion, our study suggested that the combination of network pharmacology prediction with experimental validation might offer a useful tool to characterize the molecular mechanism of AR on ALI.</p

Table_4_Network Pharmacology–Based Prediction and Pharmacological Validation of Effects of Astragali Radix on Acetaminophen-Induced Liver Injury.XLSX

Astragali Radix (AR) has been widely used in traditional Chinese medicine prescriptions for acute and chronic liver injury. However, little is known about the effects of AR on acetaminophen (APAP)-induced liver injury (ALI). In the current study, a network pharmacology–based approach was applied to characterize the action mechanism of AR on ALI. All compounds of AR were obtained from the corresponding databases, and active compounds were selected according to its oral bioavailability and drug-likeness index. The potential genes of AR were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM) and PubChem, whereas the potential genes related to ALI were obtained from Online databases (GeneCards and Online Mendelian Inheritance in Man) and Gene Expression Omnibus profiles. The enriched processes, pathways, and target genes of the diseases were analyzed by referring to the Search Tool for the Retrieval of Interacting Genes/Proteins database. A network constructed through Cytoscape software was used to identify the target proteins that connected the compounds in AR with the differential genes of ALI. Subsequently, the potential underlying action mechanisms of AR on ALI predicted by the network pharmacology analyses were experimentally validated in APAP-induced liver injury in mice and HL7702 cells incubated with APAP. The compound-target network included 181 targets, whereas the potential genes related to ALI were 4,621. A total of 49 AR–ALI crossover proteins, corresponding to 49 genes, were filtered into a protein–protein interaction network complex and designated as the potential targets of AR on ALI. Among the genes, the three highest-scoring genes, MYC, MAPK8, and CXCL8 were highly associated with apoptosis in ALI. Then in vitro and in vivo experiments confirmed that AR exhibited its prominent therapeutic effects on ALI mainly via regulating hepatocyte apoptosis related to inhibiting the expressions of MYC (c-Myc), MAPK8 (JNK1), and CXCL8 (IL-8). In conclusion, our study suggested that the combination of network pharmacology prediction with experimental validation might offer a useful tool to characterize the molecular mechanism of AR on ALI.</p