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Chikungunya virus (CHIKV) is a neglected arthropod-borne and anthropogenic alphavirus. Over the past two decades, the CHIKV distribution has undergone significant changes worldwide, from the original tropics and subtropics regions to temperate regions, which has attracted global attention. However, the interactions between CHIKV and its host remain insufficiently understood, which dampens the need for the development of an anti-CHIKV strategy. In this study, on the basis of the optimal overexpression of non-structural protein 4 (nsP4), we explore host interactions of CHIKV nsP4 using mass spectrometry-based protein-protein interaction approaches. The results reveal that some cellular proteins that interact with nsP4 are enriched in the ubiquitin-proteasome pathway. Specifically, the scaffold protein receptor for activated C kinase 1 (RACK1) is identified as a novel host interactor and regulator of CHIKV nsP4. The inhibition of the interaction between RACK1 and nsP4 by harringtonolide results in the reduction of nsP4, which is caused by the promotion of degradation but not the inhibition of nsP4 translation. Furthermore, the decrease in nsP4 triggered by the RACK1 inhibitor can be reversed by the proteasome inhibitor MG132, suggesting that RACK1 can protect nsP4 from degradation through the ubiquitin-proteasome pathway. This study reveals a novel mechanism by which the host factor RACK1 regulates CHIKV nsP4, which could be a potential target for developing drugs against CHIKV.

BackgroundPostoperative cognitive dysfunction （POCD） is a common complication in elderly patients after surgery， and has a great impact on postoperative rehabilitation of patients.ObjectiveTo explore the effect of mindfulness-based therapy on cognitive function and sleep quality in elderly patients after surgery under local anesthesia， so as to provide references for reducing their incidence risk of POCD and improving sleep quality.MethodsThe simple random sampling method was utilized to select 78 elderly patients who underwent surgery under local anesthesia in The Third Hospital of Mianyang from March 2022 to March 2023. Participants were assigned into study group and control group， each with 39 cases. All patients were subjected to conventional treatment and nursing interventions， and study group added mindfulness-based therapy on this basis. Mini-Mental State Examination （MMSE） was administered to patients on 1 day before surgery， and on the 1st， 3rd and 5th day after surgery. Pittsburgh Sleep Quality Index （PSQI） was employed on 1 day before surgery and on the 3rd day after surgery.ResultsMMSE scores revealed a significant time effect， group effect and time×group interaction effect （F=78.251， 197.071， 371.915， P

Objective To obtain the non-structure protein 14 (Nsp14) of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) with higher purity and enzymatic activity. Methods This study firstly analyzed the rare codons in the gene of nsp14 according to the codon usage bias of E. coli, followed by codon optimization. The optimized nucleotide fragment of nsp14 was cloned into four kinds of expressing vectors respectively. Comparative analysis of yield and solubility was performed among these expressed four fusion proteins. The best one was chosen for further optimization of expressing conditions. After the fusion protein was purified by glutathione affinity column, the fusion tag was removed by 3C protease, and then the protein was purified by glutathione affinity column and molecular sieve column for further analysis of enzymatic activity through urea polyacrylamide gel electrophoresis. Results Many rare codons were found in expression of SARS-CoV-2 nsp14 in E. coli, among which some rare codons were distributed in close range and tandem. The best recombinant plasmid for expressing the fusion protein was pGEX6P1-GST-OPTI-Nsp14, which gave an eptimal expression in 30 ℃ with high yield and solubility. After purification, a higher purity of Nsp14 with nuclease activity was obtained. Conclusions This study shows that the SARS-CoV-2 Nsp14 protein with nuclease activity is successfully prepared, which lays a foundation for the further research on the structure and function of SARS-CoV-2 Nsp14, and provides favorable conditions for screening antiviral drugs targeting at Nsp14 of SARS-CoV-2.

Nonalcoholic fatty liver disease (NAFLD) is a common chronic liver disease, but there is currently no effective treatment method. Probiotics have been used as an adjunct therapy for NAFLD, but the mechanism is not clear. This study used Bifidobacterium longum BL19 (BL‐19) to treat the NAFLD mice induced by a high‐fat diet, and explored the treatment mechanism through gut microbiota and serum metabolomics techniques. We found that BL‐19 effectively prevented rapid weight gain in NAFLD mice and reduced their overall food and energy intake, decreased liver inflammatory factors expressions, and increased the bile acid synthetase enzyme CYP7A1 and superoxide dismutase. After BL‐19 treatment, the abundances of butyric acid bacteria (Oscillospira and Coprococcus) in the feces of mice increased significantly, and the concentration of butyric acid also increased significantly. We believe that BL‐19 promotes the production of butyrate in the intestines, which in turn regulates the activity of CYP7A1 in the liver and bile acid synthesis, ultimately treating liver inflammation and lipid accumulation in NAFLD mice. Serum metabolomics results indicated that BL‐19 affected multiple pathways related to inflammation and lipid metabolism in NAFLD mice. These findings suggest that BL‐19 shows promise as an adjunct therapy for NAFLD, as it can significantly improve oxidative stress, reduce inflammation in the liver, and decrease lipid accumulation. [ABSTRACT FROM AUTHOR]

Straw return is an effective measure to increase soil sustainability. However, few studies have examined the effects of different straw return methods on soil structure, soil organic carbon content and maize yield or the potential relationships between those variables. Therefore, we developed a field orientation experiment to study the effects of different straw return methods on soil porosity, soil aggregate stability, the soil organic carbon content and maize yield. Four treatments were established: flat no-tillage with full straw mulching (FM), ridge no-tillage with full straw mulching (LM), rotary tillage with full straw incorporation (LX), and conventional tillage without straw (CK) as the control treatment. Compared with those of the CK treatment, the soil porosities (f) in the FM, LM and LX treatments significantly increased by 6.7%, 8.8% and 7.9%, respectively; the soil aggregate destruction rates (PAD) decreased by 17.3%, 34.3% and 16.9%, respectively. In addition, the FM, LM and LX treatments effectively increased the mean mass diameters (MWDs) of the soil aggregates and the soil organic carbon content. Compared with those in the CK treatment, the three-year average yields in the FM, LM and LX treatments significantly increased by 5.2%, 7.2% and 4.1%, respectively. Moreover, the f, MWD, soil organic carbon content and corn yield were positively correlated. Our study indicates that the LM treatment was most effective in improving soil structure and increasing soil organic carbon content with corn yield. [ABSTRACT FROM AUTHOR]

Simple Summary: Tyrosine kinase inhibitors (TKIs) have demonstrated effectiveness in a variety of malignancies. As is the case for many different classes of drugs, tyrosine kinase inhibitors induce autophagy in various tumor cell models. Autophagy is a cellular degradative machinery that can be protective or cytotoxic to the cells, and in some cases, autophagy has no detectable influence on cell sensitivity to chemotherapy. This review demonstrates that cytoprotective and cytotoxic autophagy are the main forms induced by TKIs and that targeting or modulating autophagy can potentially enhance the tumor cell response to tyrosine kinase inhibitors. Tyrosine kinase inhibitors (TKIs) represent a relatively large class of small-molecule inhibitors that compete with ATP for the catalytic binding site of tyrosine kinase proteins. While TKIs have demonstrated effectiveness in the treatment of multiple malignancies, including chronic myelogenous leukemia, gastrointestinal tumors, non-small cell lung cancers, and HER2-overexpressing breast cancers, as is almost always the case with anti-neoplastic agents, the development of resistance often imposes a limit on drug efficacy. One common survival response utilized by tumor cells to ensure their survival in response to different stressors, including anti-neoplastic drugs, is that of autophagy. The autophagic machinery in response to TKIs in multiple tumor models has largely been shown to be cytoprotective in nature, although there are a number of cases where autophagy has demonstrated a cytotoxic function. In this review, we provide an overview of the literature examining the role that autophagy plays in response to TKIs in different preclinical tumor model systems in an effort to determine whether autophagy suppression or modulation could be an effective adjuvant strategy to increase efficiency and/or overcome resistance to TKIs. [ABSTRACT FROM AUTHOR]

Timely and accurate mapping of rice distribution is crucial to estimate yield, optimize agriculture spatial patterns, and ensure global food security. Feature selection (FS) methods have significantly improved computational efficiency by reducing redundancy in spectral and temporal feature sets, playing a vital role in identifying and mapping paddy rice. However, the optimal feature sets selected by existing methods suffer from issues such as information redundancy or local optimality, limiting their accuracy in rice identification. Moreover, the effects of these FS methods on rice recognition in various machine learning classifiers and regions with different climatic conditions and planting structures is still unclear. To overcome these limitations, we conducted a comprehensive evaluation of the potential applications of major FS methods, including the wrapper method, embedded method, and filter method for rice mapping. A novel hierarchical lustering sequential forward selection (HCSFS) method for precisely extracting the optimal feature set for rice identification is proposed. The accuracy of the HCSFS and other FS methods for rice identification was tested with nine common machine learning classifiers. The results indicated that, among the three FS methods, the wrapper method achieved the best rice mapping performance, followed by the embedded method, and lastly, the filter method. The new HCSFS significantly reduced redundant features compared with eleven typical FS methods, demonstrating higher precision and stability, with user accuracy and producer accuracy exceeding 0.9548 and 0.9487, respectively. Additionally, the spatial distribution of rice maps generated using the optimal feature set selected by HCSFS closely aligned with actual planting patterns, markedly outperforming existing rice products. This research confirms the effectiveness and transferability of the HCSFS method for rice mapping across different climates and cultivation structures, suggesting its enormous potential for classifying other crops using time-series remote sensing images. [ABSTRACT FROM AUTHOR]