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Purpose: To systematically study and predict the therapeutic targets and signaling pathways of Hippocampus (HPC) against chronic kidney disease (CKD) using network pharmacology.Methods: By combining database mining, literature searching, screening of disease targets, and network construction, the effects of various components of HPC on several proteins related to CKD were predicted and the active compounds were screened. Genes related to the selected compounds were linked using the SEA database. The correlation between CKD and genes was determined using OMIM, DisGenNet, and GeneCards databases. Pathway-enrichment analyses of overlapping genes were undertaken using online databases.Results: A total of 144 compounds in HPC were identified. Analyses of clusters suggest that the active components of HPC and the target genes against the inflammation caused by CKD were due to 10 compounds and 25 genes. Metascape results showed that these HPC targets are related to CKD inflammation.Conclusion: The active components of HPC and the target genes against CKD inflammation are involved in multiple signaling pathways, such as AGE-RAGE, TLR, TNF, and NF-κB. This work provides scientific evidence to support the clinical use of HPC against CKD.

In this paper, a finite-time trajectory tracking control for unmanned surface vessel with error constraints and input saturations is proposed. We take the limited actuator capability into account and employ the hyperbolic tangent function to address the saturation problem, which is converted into the unknown input gains. A tan-type barrier Lyapunov function tackles the error constraints, where error variables remain within the predefined bounds. In addition, the neural networks are utilized for model uncertainties and external disturbances. We present a semi-globally uniformly bounded control method, and develop a finite-time control approach subsequently. Finally, the effectiveness of the proposed strategies is verified by the simulation studies.

Glioma is the most common malignant tumor of the central nervous system (CNS). Therapeutic efficacy of glioma treatment is greatly limited by the blood-brain barrier (BBB) and blood-brain tumor barrier (BBTB), which restrict the passage of most drugs into the brain and tumors. Developing drug delivery systems that cross the BBB and BBTB will aid in the treatment of glioma and malignant brain metastases. One emerging solution is to identify peptide vectors that penetrate the BBB/BBTB. Herein, a novel BBB/BBTB-penetrating peptide was identified from the phage-displayed peptide library. Peptide-drug conjugates (PDCs) were derived and applied to treat glioma and breast cancer brain metastases. Antitumor activity was achieved in both tumor models with synergistic effects when combined with the currently used chemotherapy drug temozolomide. The peptide reported herein can serve as a universal vector for shuttling compounds across the BBB; therefore, it may have wide applications for treating brain tumors and other CNS diseases.

The unmanned surface vessel (USV) plays an important role in smart ocean. This study proposes an adaptive fault-tolerant tracking control for USVs in the presence of input saturations and error constraints. A tan-type barrier Lyapunov function is utilised for the error constraints and the neural networks are employed to treat the model uncertainty. Moreover, the adaptive technique combined with the backstepping method not only enables the actuator fault-tolerant controller to address the fault effects but also handles the external disturbances and input saturations. The proposed control approach can track the desired trajectory with error constraints and the system is guaranteed to be uniformly bounded under certain actuator failure. Numerical simulation is carried out to verify the effectiveness of this control strategy.

Additional file 7: Table S1. Summary of the sequences and richness and diversity indexes of the bacteria in the fruiting bodies. Table S2. Summary of the sequences and richness and diversity indexes of the bacteria in the soil microhabitat. Table S3. Summary of the sequences and richness and diversity indexes of the fungi in the fruiting bodies. Table S4. Summary of the sequences and richness and diversity indexes the fungi in the soil microhabitat.

Additional file 12: Table S14. Taxonomic summary of 4 supercore microorganisms.

Additional file 11: Table S13. Distribution of the distinct bacterial functions during O. highlandensis maturation.

Additional file 2: Fig. S2. Rarefaction curves of the bacterial (A) and fungal (B) communities collected from fruiting bodies of O. highlandensis and the surrounding soil.

Additional file 5: Fig. S5. Density plots of the NSTI values from the function prediction process performed with PICRUSt2 software.

Additional file 10: Table S9. Relative abundances of the bacterial phyla and classes belonging to the Proteobacteria in all the fruiting body samples. Table S10. The relative abundances of the bacterial phyla and classes belonging to the Proteobacteria in all the soil microhabitat samples. Table S11. The relative abundances of the fungal phyla in all the fruiting body samples. Table S12. The relative abundances of the fungal phyla in all the soil microhabitat samples.

Additional file 1: Fig. S1. Abiotic environmental variation in the O. highlandensis habitats featured in this study. The TN (total nitrogen), TP (total phosphorus), TK (total potassium), TC (total carbon), DOC (dissolved organic carbon), C/N (carbon-nitrogen ratio), humidity (%), and pH of each sampling site are shown.

Additional file 9: Table S8. Results of a pairwise permutational MANOVA on the beta diversity of the bacterial community composition in the fruiting body. ​P-values result from 999 permutations of a Bray-Curtis dissimilarity matrix. The bold values indicate statistically significant results.

Additional file 8: Table S5. Pairwise comparisons of the Shannon index and Evenness parameter among the bacterial groups inhabiting the soil microhabitat. The bold values represent statistically significant results. Table S6. Pairwise comparisons of the Shannon index and evenness parameter among the fungal groups inhabiting the fruiting body. The bold values indicate statistically significant results. Table S7. Pairwise comparisons of the Shannon index and Evenness parameter among the fungal groups inhabiting the soil microhabitat. The bold values represent statistically significant results.

Additional file 3: Fig. S3. Box plot of multivariate alpha dispersions of the microbial composition. (A) Comparisons of the bacterial alpha dispersions (Evenness parameter) grouped with multivariate variables. (B) Comparisons of the fungal alpha dispersions (Evenness parameter) grouped with multivariate variables.

In this paper, a trajectory tracking control strategy based on anti-windup compensator is proposed for unmanned surface vessels subject to input saturation and full-state constraints. The saturation problem is handled by the anti-windup compensator, which utilizes an auxiliary system to compensate for the saturation difference directly. In addition, the barrier Lyapunov function is employed to prevent states from violating the constraints. It is proved that the proposed control strategy can achieve the semi-global uniform boundedness of the closed-loop system through Lyapunov stability theory. Finally, simulation results further demonstrate its excellent performance.

This article talks about using chrt 0.35 N well technology to design a bandgap reference with low temperature drift, the circuit uses two resistances with different temperature characteristic series in the PTAT current in order to provide curve compensation. Then we use the spectre to simulate it in the temperature range from -20°C to 100°C and get a good result with the temperature coefficient is 2.27 ppm/.

This article investigates the trajectory tracking control problem for unmanned surface vessels with input saturation and full-state constraints. The barrier Lyapunov function is used to solve the problem of state constraints, and the adaptive method is employed to handle the unknown random disturbances and saturation problems. The proposed control approach can guarantee that the control law and signals of closed-loop system are uniformly bounded and achieve the asymptotic tracking. Finally, simulation studies are provided to show the effectiveness of the proposed method.