Effects of Different Mulching Practices on Soil Environment and Fruit Quality in Peach Orchards.

Mulching practices have been used to improve peach growth and production across the globe. However, the impact of mulching on the physiochemical properties and soil characteristics of orchards remains largely unknown. This study aimed to decipher the impacts of various mulching patterns on the soil environment and the quality of Prunus persica fruit in "Zijinhuangcui". Three treatments were set up, which included black ground fabric mulch (BF) and two living grass mulch treatments (HV: hairy vetch and RG: ryegrass). The results showed that different mulching treatments have different effects on soil, plant growth, and fruit quality. Living grass mulch treatments, especially the HV treatment, significantly improved soil nutrients by enhancing nitrogen-related indicators. Of note, the BF treatment had higher total phosphorus and available phosphorus contents than the HV and RG treatments. The HV treatment had the highest relative abundance of Proteobacteria (33.49%), which is associated with symbiotic nitrogen fixation, followed by RG (25.62%), and BF (22.38%) at the young fruit stage. Similarly, the abundance of Terrimonas, which has a unique nitrogen fixation system at the genus level, was significantly higher in the living grass mulch (HV, 1.30-3.13% and RG, 2.27-4.24%) than in the BF treatment. Living grass mulch also promoted tree growth, increased fruit sugar content, sugar-related components, and sugar-acid ratio, and reduced the acid content. Collectively, the findings of this study show that living grass mulch can promote tree growth and improve fruit quality by improving soil fertility, bacterial diversity, and richness.

Comprehensive analysis of the role of CXCL family members in clear cell renal cell carcinoma.

Background CXCLs are a group of low-molecular-weight growth factors secreted by cells, mainly through G protein-coupled receptors for signal transduction and induction of cell chemotactic motility. Their abnormal expression is linked to immune cell activity in cancer and tumor growth and progression. However, the differential expressions of CXCLs in ccRCC, prognostic prospects, and immune infiltration have not been clearly explored. Objective This study aimed to analyze the expression profile of CXCL family members in clear cell renal cell carcinoma, its prognostic significance, and the correlation between CXCL family members and tumor immunity. Methods The expression difference of CXCLs between ccRCC and normal renal tissues was analyzed by the TCGA database. The prognostic value of CXCLs in ccRCC was analyzed by the Kaplan-Meier Plotter. The copy number variation (CNV) of CXCLs in ccRCC was explored through the GSCA website. The cBioPortal online tool was used to screen out 355 co-expressed genes significantly related to CXCLs. The protein-protein interaction network of co-expressed genes was constructed using the STRING database, and the pathways that significantly enriched these genes were explored using Metascape. We then used the least absolute shrinkage and selection operator (LASSO) regression analysis to develop a predictive risk model for ccRCC patients. The relationship between CXCLs and tumor immune cell infiltration was analyzed. Finally, drugs interacting with CXCLs were analyzed using the DGIdb database. Results It was observed that mRNA expression levels of CXCL-2,-3,-4,-5,-9,-10,-11,-13, and -16 in the tissue of KIRC were higher than normal KIRC tissue. In contrast, CXCL12 expression decreased. Furthermore, CXCL5,-9,-10,-11,-12, and -13 mRNA expression was significantly correlated with the clinical stage. In KIRC patients, elevated CXCL1,-2,-5, and -13 expression was associated with shorter overall survival, while elevated CXCL14 expression was associated with a better prognosis. Through LASSO regression analysis, we obtained a 5-gene prognostic signature. This prognostic feature is associated with the infiltration of multiple immune cells. Conclusion In this study, we evaluated the expression levels of CXCL genes in KIRC and their prognostic potential in KIRC. CXCL-5,-9,-10,-11,-12, and -13 may be associated with ccRCC progression, and CXCL-1,-2,-5,-13, and -14 may be potential prognostic markers.

High C1QTNF1 expression mediated by potential ncRNAs is associated with poor prognosis and tumor immunity in kidney renal clear cell carcinoma.

Background: Kidney renal clear cell carcinoma (KIRC) originates from proximal tubular cells and is the most common subtype of renal cell carcinoma. KIRC is characterized by changes in lipid metabolism, and obesity is a risk factor for it. C1q And TNF Related 1 (C1QTNF1), a novel adipokine and member of the C1q and TNF-related protein (CTRP) family, has been shown to affect the progression of various cancers. However, the role of C1QTNF1 in KIRC has not been studied. Methods: The Wilcoxon rank sum test was used to analyze the expression of C1QTNF1 in KIRC tissues and normal tissues. The relationship between clinicopathological features and C1QTNF1 levels was also examined by logistic regression and the Wilcoxon rank sum test. In addition, the effect of C1QTNF1 on the prognosis of KIRC patients was analyzed by Kaplan-Meier (KM). The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze the potential signaling pathways and biological functions of differential genes. A nomogram was constructed to predict the prognosis of KIRC patients. Spearman correlation analysis was performed to determine the association between C1QTNF1 expression and immune cell infiltration and immune checkpoint genes. The upstream miRNAs and lncRNAs of C1QTNF1 were predicted by the ENCORI online tool. Finally, we examined the proliferation, invasion, and migration abilities of KIRC cells after C1QTNF1 knockdown. Results: The expression of C1QTNF1 in KIRC tissues was significantly higher than in normal renal tissues. Patients with higher C1QTNF1 expression had a poor prognosis, a finding supported by Kaplan-Meier survival analysis. C1QTNF1 expression was significantly correlated with TNM and pathologic stages, age, and gender (p < 0.05). The C1QTNF1 expression level was significantly correlated with immune cell infiltration and immune checkpoint genes in KIRC. Additionally, high C1QTNF1 expression was associated with poor prognosis in stage I and II, T1 and T2, T3 and T4, N0, and M0 patients (HR > 1, p < 0.05). The calibration diagram shows that the C1QTNF1 model has effective predictive performance for the survival of KIRC patients. Knockdown of C1QTNF1 inhibited KIRC cell proliferation, cell migration, and cell invasion. In addition, CYTOR and AC040970.1/hsa-miR-27b-3p axis were identified as the most likely upstream ncRNA-related pathways of C1QTNF1 in KIRC. Conclusion: In conclusion, our study suggests that high expression of C1QTNF1 is associated with KIRC progression and immune infiltration. The increased expression of C1QTNF1 suggests a poor prognosis in KIRC patients.

Sphingosine kinase 1 regulates lipid metabolism to promote progression of kidney renal clear cell carcinoma.

PURPOSE: To detect the expression of sphingosine kinase 1 (SPHK1) in clear cell renal cell carcinoma (ccRCC) and explore its biological role in the occurrence and development of ccRCC through regulation of fatty acid metabolism. METHODS: Using the Cancer Genome Atlas database, SPHK1 expression and its clinical significance were detected in clear cell renal cell carcinoma. Immunohistochemistry was performed to detect SPHK1 expression in RCC samples in our hospital. The connection between the SPHK1 levels and clinicopathological features of patients was assessed. Nile Red was used to detect fatty acids in cells. Cell Counting Kit-8 and 5-ethynyl-2'-deoxyuridine assays were performed to determine the effect of SPHK1 on renal cell viability and proliferation, respectively. Additionally, the effects of SPHK1 on the proliferation and metastasis of ccRCC were studied using wound healing and Transwell assays. Fatty acids were added exogenously in recovery experiments and western blotting was performed to determine the effect of SPHK1 on fatty acid metabolism in ccRCC. Finally, the effects of SPHK1 on tumor growth were investigated in a xenograft model. RESULTS: Bioinformatics analysis revealed that SPHK1 expression was upregulated in kidney RCC. OverSPHK1 expression was associated with poor prognosis for ccRCC patients. High SPHK1 expression was detected in human ccRCC. SPHK1 expression was related to clinicopathological features, such as tumor size and Furman grade. Additionally, cell proliferation, migration, and invasion were inhibited in ccRCC cells with low SPHK1 expression. In rescue experiments, proliferation, migration, and invasion were restored. In vivo, reduced SPHK1 levels correlated with lower expression of fatty acid synthase, stearoyl-CoA desaturase 1, and acetyl CoA carboxylase, and slowed tumor growth. CONCLUSIONS: SPHK1 is abnormally overexpressed in human ccRCC. Patients with ccRCC may benefit from treatments that target SPHK1, which may also serve as a prognostic indicator.

Microrobot Path Planning Based on the Multi-Module DWA Method in Crossing Dense Obstacle Scenario.

A hard issue in the field of microrobots is path planning in complicated situations with dense obstacle distribution. Although the Dynamic Window Approach (DWA) is a good obstacle avoidance planning algorithm, it struggles to adapt to complex situations and has a low success rate when planning in densely populated obstacle locations. This paper suggests a multi-module enhanced DWA (MEDWA) obstacle avoidance planning algorithm to address the aforementioned issues. An obstacle-dense area judgment approach is initially presented by combining Mahalanobis distance, Frobenius norm, and covariance matrix on the basis of a multi-obstacle coverage model. Second, MEDWA is a hybrid of enhanced DWA (EDWA) algorithms in non-dense areas with a class of two-dimensional analytic vector field methods developed in dense areas. The vector field methods are used instead of the DWA algorithms with poor planning performance in dense areas, which greatly improves the passing ability of microrobots over dense obstacles. The core of EDWA is to extend the new navigation function by modifying the original evaluation function and dynamically adjusting the weights of the trajectory evaluation function in different modules using the improved immune algorithm (IIA), thus improving the adaptability of the algorithm to different scenarios and achieving trajectory optimization. Finally, two scenarios with different obstacle-dense area locations were constructed to test the proposed method 1000 times, and the performance of the algorithm was verified in terms of step number, trajectory length, heading angle deviation, and path deviation. The findings indicate that the method has a smaller planning deviation and that the length of the trajectory and the number of steps can both be reduced by about 15%. This improves the ability of the microrobot to pass through obstacle-dense areas while successfully preventing the phenomenon of microrobots going around or even colliding with obstacles outside of dense areas.

Metacognitive prompts and numerical ordinality in solving word problems: An eye-tracking study.

BACKGROUND: The ability to translate concrete manipulatives into abstract mathematical formulas can aid in the solving of mathematical word problems among students, and metacognitive prompts play a significant role in enhancing this process. AIMS: Based on the concept of semantic congruence, we explored the effects of metacognitive prompts and numerical ordinality on information searching and cognitive processing, throughout the process of solving mathematical word problems among primary school students in China. SAMPLE: Participants included 73 primary school students (38 boys and 35 girls) with normal or corrected visual acuity. METHODS: This study was based on a 2 (prompt information: no-prompt, metacognitive-prompt) × 2 (number attribute: cardinal number, ordinal number) mixed experimental design. We analysed multiple eye-movement indices, such as fixation duration, saccadic amplitude, and pupil size, since they pertained to the areas of interest. RESULTS: When solving both types of problems, pupil sizes were significantly smaller under the metacognitive-prompt condition compared with the no-prompt condition, and shorter dwell time for specific sentences, conditional on metacognitive prompts, indicated the optimization of the presented algorithm. Additionally, the levels of fixation durations and saccadic amplitudes were significantly higher when solving ordinal number word problems compared with solving ordinal number problems, indicating that primary school students were less efficient in reading and faced increased levels of difficulty when solving ordinal number problems. CONCLUSIONS: The results indicate that for Chinese upper-grade primary school students, cognitive load was lower in the metacognitive prompting condition and when solving cardinal problems, and higher when solving ordinal problems.

Meta-analysis of the efficacy and adverse drug reactions of adrenergic alpha-antagonists in treating children with ureteral calculi.

This meta-analysis investigated the efficacy and adverse drug reactions (ADRs) of three different adrenergic alpha-antagonists during the treatment of pediatric ureteral stones. Studies were retrieved from MEDLINE, EMBASE, and the Cochrane Controlled Trial Registry until January 2022. We identified 7 articles, including six RCTs and one cohort study. 610 children received either adrenergic alpha-antagonists or placebo. The results confirmed that the three different adrenergic alpha-antagonists could significantly increase the ureteral calculi expulsive rate and shorten the ureteral calculi expulsive time, regardless of the size of the stone "<5 mm" or "5-10 mm". Subgroup analysis suggested that all three adrenergic alpha-antagonists increased the ureteral calculi expulsive rate. Tamsulosin and silodosin also have the effect of shortening ureteral calculi expulsive time, while doxazosin has an insignificant effect on ureteral calculi expulsive time. Besides, tamsulosin and silodosin obviously reduced the number of pain episodes caused by ureteral calculi in children. We analyzed the treatment-emergent adverse events (TEAEs) caused by the treatment of three different adrenergic alpha-antagonists to explore their ADRs. The probability of ADRs was increased after treatment with adrenergic alpha-antagonists. Further subgroup analysis revealed the application of tamsulosin was positively correlated with ADRs in children with ureteral calculi, while the application of doxazosin and silodosin had no statistically significant effect on the probability of TEAEs. In a conclusion, this article systematically analyzed the efficacy and ADRs of three different adrenergic alpha-antagonists, and provided reference and guidance for the application of adrenergic alpha-antagonists to treat children ureteral calculi.

Low expression of SLC34A1 is associated with poor prognosis in clear cell renal cell carcinoma.

OBJECTIVE: Clear cell renal cell carcinoma (ccRCC) is a malignant renal tumor that is highly prone to metastasis and recurrence. The exact pathogenesis of this cancer is still not well understood. This study aimed to identify novel hub genes in renal clear cell carcinoma and determine their diagnostic and prognostic value. METHODS: Intersection genes were obtained from multiple databases, and protein-protein interaction analysis and functional enrichment analysis were performed to identify key pathways related to the intersection genes. Hub genes were identified using the cytoHubba plugin in Cytoscape. GEPIA and UALCAN were utilized to observe differences in mRNA and protein expression of hub genes between KIRC and adjacent normal tissues. The Wilcoxon rank sum test was used to analyze hub gene levels between paired KIRC and matched non-cancer samples. IHC results were obtained from the HPA online database, and according to the median gene expression level, they were divided into a high-expression group and a low-expression group. The correlation of these groups with the prognosis of KIRC patients was analyzed. Logistic regression and the Wilcoxon rank sum test were used to test the relationship between SLC34A1 level and clinicopathological features. The diagnostic value of SLC34A1 was evaluated by drawing the receiver operating characteristic (ROC) curve and calculating the area under the curve (AUC). Cox regression analysis was used to analyze the relationship between clinicopathological features, SLC34A1 expression, and KIRC survival rate. LinkedOmics was used to obtain the genes most related to SLC34A1 and their functional enrichment. Genetic mutations and methylation levels of SLC34A1 in KIRC were obtained from the cBioPortal website and the MethSurv website, respectively. RESULTS: Fifty-eight ccRCC differential genes were identified from six datasets, and they were mainly enriched in 10 functional items and 4 pathways. A total of 5 hub genes were identified. According to the GEPIA database analysis, low expression of SLC34A1, CASR, and ALDOB in tumors led to poor prognosis. Low expression of SLC34A1 mRNA was found to be related to clinicopathological features of patients. SLC34A1 expression in normal tissues could accurately identify tumors (AUC 0.776). SLC34A1 was also found to be an independent predictor of ccRCC in univariate and multivariate Cox analyses. The mutation rate of the SLC34A1 gene was 13%. Eight of the 10 DNA methylated CpG sites were associated with the prognosis of ccRCC. SLC34A1 expression in ccRCC was positively correlated with B cells, eosinophils, neutrophils, T cells, TFH, and Th17 cells, and negatively correlated with Tem, Tgd, and Th2 cells. CONCLUSION: The expression level of SLC34A1 in KIRC samples was found to be decreased, which predicted a decreased survival rate of KIRC. SLC34A1 may serve as a molecular prognostic marker and therapeutic target for KIRC patients.

Establishment of a new prognostic risk model of MAPK pathway-related molecules in kidney renal clear cell carcinoma based on genomes and transcriptomes analysis.

Purpose: The mitogen-activated protein kinase (MAPK) signaling pathway is often studied in oncology as the most easily mentioned signaling pathway. This study aims to establish a new prognostic risk model of MAPK pathway related molecules in kidney renal clear cell carcinoma (KIRC) based on genome and transcriptome analysis. Methods: In our study, RNA-seq data were acquired from the KIRC dataset of The Cancer Genome Atlas (TCGA) database. MAPK signaling pathway-related genes were obtained from the gene enrichment analysis (GSEA) database. We used "glmnet" and the "survival" extension package for LASSO (Least absolute shrinkage and selection operator) regression curve analysis and constructed a prognosis-related risk model. The survival curve and the COX regression analysis were used the "survival" expansion packages. The ROC curve was plotted using the "survival ROC" extension package. We then used the "rms" expansion package to construct a nomogram plot. We performed a pan-cancer analysis of CNV (copy number variation), SNV (single nucleotide variant), drug sensitivity, immune infiltration, and overall survival (OS) of 14 MAPK signaling pathway-related genes using several analysis websites, such as GEPIA website and TIMER database. Besides, the immunohistochemistry and pathway enrichment analysis used The Human Protein Atlas (THPA) database and the GSEA method. Finally, the mRNA expression of risk model genes in clinical renal cancer tissues versus adjacent normal tissues was further verified by real-time quantitative reverse transcription (qRT-PCR). Results: We performed Lasso regression analysis using 14 genes and created a new KIRC prognosis-related risk model. High-risk scores suggested that KIRC patients with lower-risk scores had a significantly worse prognosis. Based on the multivariate Cox analysis, we found that the risk score of this model could serve as an independent risk factor for KIRC patients. In addition, we used the THPA database to verify the differential expression of proteins between normal kidney tissues and KIRC tumor tissues. Finally, the results of qRT-PCR experiments suggested large differences in the mRNA expression of risk model genes. Conclusions: This study constructs a KIRC prognosis prediction model involving 14 MAPK signaling pathway-related genes, which is essential for exploring potential biomarkers for KIRC diagnosis.

Emerging landscape of circFNDC3B and its role in human malignancies.

In recent years, more attention has been paid to expanding the abundance of Circular RNAs (circRNAs), while the circRNAs that have been found to have significant functions have not been studied in different diseases. CircFNDC3B is one of the most researched circRNAs generated from fibronectin type III domain-containing protein 3B (FNDC3B) gene. Accumulating researches have reported the multiple functions of circFNDC3B in different cancer types and other non-neoplastic diseases, and predicted that circFNDC3B might be a potential biomarker. Notably, circFNDC3B can play roles in different diseases by binding to various microRNAs (miRNAs), binding to RNA-binding proteins (RBPs), or encoding functional peptides. This paper systematically summarizes the biogenesis and function of circRNAs, reviews and discusses the roles and molecular mechanisms of circFNDC3B and its target genes in different cancers and non-neoplastic diseases, which will do favor to broaden our comprehension of the function of circRNAs and facilitate subsequent research on circFNDC3B.

Comprehensive Multiomics Analysis Reveals Potential Diagnostic and Prognostic Biomarkers in Adrenal Cortical Carcinoma.

Adrenal cortical carcinoma (ACC) is a severe malignant tumor with low early diagnosis rates and high mortality. In this study, we used a variety of bioinformatic analyses to find potential prognostic markers and therapeutic targets for ACC. Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) data sets were used to perform differential expressed analysis. WebGestalt was used to perform enrichment analysis, while String was used for protein-protein analysis. Our study first detected 28 up-regulation and 462 down-regulation differential expressed genes through the GEO and TCGA databases. Then, GO functional analysis, four pathway analyses (KEGG, REACTOME, PANTHER, and BIOCYC), and protein-protein interaction network were performed to identify these genes by WebGestalt tool and KOBAS website, as well as String database, respectively, and finalize 17 hub genes. After a series of analyses from GEPIA, including gene mutations, differential expression, and prognosis, we excluded one candidate unrelated to the prognosis of ACC and put the remaining genes into pathway analysis again. We screened out CCNB1 and NDC80 genes by three algorithms of Degree, MCC, and MNC. We subsequently performed genomic analysis using the TCGA and cBioPortal databases to better understand these two hub genes. Our data also showed that the CCNB1 and NDC80 genes might become ACC biomarkers for future clinical use.

ARL4C Regulates the Progression of Clear Cell Renal Cell Carcinoma by Affecting the Wnt/ß-Catenin Signaling Pathway.

Purpose: To investigate the expression of the ADP-ribosylation factor (ARF)-like proteins (ARLs) and ARL4C in clear cell renal cell carcinoma (ccRCC) based on bioinformatics analysis and experimentally determine the effect and mechanism of ARL4C on cellular properties involved in ccRCC progression. Methods: After downloading the data of cancer patients from the TCGA database, we used various bioinformatics analysis websites and methods to analyze the expression and function of ARLs and ARL4C. The differential expression of ARL4C in clinical renal cancer tissues versus adjacent normal tissues was further verified using immunohistochemistry and real-time quantitative reverse-transcription (qRT-PCR). qRT-PCR was used to explore the expression of ARL4C mRNA in normal renal cells versus different ccRCC cell lines, and the protein expression of ARL4C was further verified using western blotting. CCK-8, colony formation, and EdU assays were used to determine the effect of ARL4C knockdown on ccRCC cell proliferation. We also used wound healing and Transwell assays to analyze the changes in ccRCC cell migration and invasion following ARL4C knockdown. Finally, we used western blotting to probe the molecular mode of action of ARL4C in ccRCC cells after exposure to Wnt signaling pathway agonists. Results: Biological function analysis showed that methylation of ARL4C and changes in immune cell infiltration and targeted drug sensitivity caused by altered ARL4C expression affected the prognosis of ccRCC. Further bioinformatics analysis suggested that the expression of ARL4C mRNA was increased in ccRCC, and this was associated with a poor prognosis in ccRCC patients. Increased expression of ARL4C was further verified using qRT-PCR and western blotting of human ccRCC tissue samples. Downregulation of ARL4C significantly inhibited the proliferation, migration, and invasion of ccRCC cells, and activation of the Wnt/ß-catenin pathway promoted the expression of ARL4C. As an essential downstream effector of the Wnt signaling pathway, ARL4C increased the expression of cyclin D1 and c-myc, thereby increasing the ability of the cells to undergo epithelial-mesenchymal transition (EMT) and ccRCC progression. Conclusions: As a critical factor in the Wnt/ß-catenin pathway, ARL4C regulates EMT and progression in ccRCC.

The Role of ERBB Signaling Pathway-Related Genes in Kidney Renal Clear Cell Carcinoma and Establishing a Prognostic Risk Assessment Model for Patients.

Objective: We aimed to investigate the potential role of ERBB signaling pathway-related genes in kidney renal clear cell carcinoma (KIRC) and establish a new predictive risk model using various bioinformatics methods. Methods: We downloaded the KIRC dataset and clinicopathological information from The Cancer Genome Atlas database. Univariate Cox analysis was used to identify essential genes significantly associated with KIRC progression. Next, we used the STRING website to construct a protein-protein interaction network of ERBB signaling pathway-related molecules. We then used the least the absolute shrinkage and selection operator (LASSO) regression analysis to build a predictive risk model for KIRC patients. Next, we used multiple bioinformatics methods to analyze the copy number variation, single-nucleotide variation, and overall survival of these risk model genes in pan-cancer. At last, we used the Genomics of Drug Sensitivity in Cancer to investigate the correlation between the mRNA expression of genes associated with this risk model gene and drug sensitivity. Results: Through the LASSO regression analysis, we constructed a novel KIRC prognosis-related risk model using 12 genes: SHC1, GAB1, SOS2, SRC, AKT3, EREG, EIF4EBP1, ERBB3, MAPK3, transforming growth factor-alpha, CDKN1A, and PIK3CD. Based on this risk model, the overall survival rate of KIRC patients in the low-risk group was significantly higher than that in the high-risk group (p = 1.221 × 10-15). Furthermore, this risk model was associated with cancer metastasis, tumor size, node, stage, grade, sex, and fustat in KIRC patients. The receiver operating characteristic curve results showed that the model had better prediction accuracy. Multivariate Cox regression analysis showed that the model's risk score was an independent risk factor for KIRC. The Human Protein Atlas database was used to validate the protein expression of risk model-associated molecules in tumors and adjacent normal tissues. The validation results were consistent with our previous findings. Conclusions: We successfully established a prognostic-related risk model for KIRC, which will provide clinicians with a helpful reference for future disease diagnosis and treatment.

AUP1 regulates lipid metabolism and induces lipid accumulation to accelerate the progression of renal clear cell carcinoma.

Lipid metabolic reprogramming is a prominent feature of clear cell renal cell carcinoma (ccRCC). Lipid accumulation affects cellular energy homeostasis, biofilm synthesis, lipid signal transduction, and phenotypic transformation in ccRCC. Herein, a prognostic-related model was constructed, and the prognostic utility of AUP1, a lipid droplet-regulating very low-density lipoprotein assembly factor, in ccRCC was determined through multiparameter analysis. AUP1 expression was significantly higher in clinical samples than in normal tissues and was closely associated with the clinical stage. The inhibition of AUP1 expression impaired the proliferation, migration, and invasion of ACHN and A498 ccRCC cells in vitro and in vivo. RNA-seq analysis revealed that AUP1 inhibition can significantly reduce the contents of intracellular triglyceride and cholesterol and regulate cell growth by cell cycle arrest, promoting apoptosis and reversing epithelial-mesenchymal transition. AUP1 regulated the synthesis of cholesterol esters and fatty acids (FAs) in ccRCC cells by targeting sterol O-acyltransferase 1 and partially promoted the progression of ccRCC. AUP1 also induced lipid accumulation in ccRCC by promoting the de novo synthesis of FAs (inhibiting protein kinase AMP-activated catalytic subunit alpha 2), inhibiting the rate-limiting enzyme of FA ß oxidation (carnitine palmitoyltransferase 1A), regulating the key enzyme of lipolysis (monoglyceride lipase, MGLL), and inhibiting the lipid transporter StAR-related lipid transfer domain containing 5 (STARD5). However, it did not affect the intracellular cholesterol synthesis pathway. The differential expression and prognostic significance of MGLL and STARD5 in ccRCC should be further studied. AUP1 may serve as a new and effective potential target and prognostic marker for ccRCC.

A new prognostic risk model based on autophagy-related genes in kidney renal clear cell carcinoma.

This study aimed to explore the potential role of autophagy-related genes in kidney renal clear cell carcinoma (KIRC) and develop a new prognostic-related risk model. In our research, we used multiple bioinformatics methods to perform a pan-cancer analysis of the CNV, SNV, mRNA expression, and overall survival of autophagy-related genes, and displayed the results in the form of heat maps. We then performed cluster analysis and LASSO regression analysis on these autophagy-related genes in KIRC. In the cluster analysis, we successfully divided patients with KIRC into five clusters and found that there was a clear correlation between the classification and two clinicopathological features: tumor, and stage. In LASSO regression analysis, we used 13 genes to create a new prognostic-related risk model in KIRC. The model showed that the survival rate of patients with KIRC in the high-risk group was significantly lower than that in the low-risk group, and that there was a correlation between this grouping and the patients' metastasis, tumor, stage, grade, and fustat. The results of the ROC curve suggested that this model has good prediction accuracy. The results of multivariate Cox analysis show that the risk score of this model can be used as an independent risk factor for patients with KIRC. In summary, we believe that this research provides valuable data supporting future clinical treatment and scientific research.

A New Survival Model Based on Cholesterol Biosynthesis-Related Genes for Prognostic Prediction in Clear Cell Renal Cell Carcinoma.

In our study, the value of cholesterol biosynthesis is related to clinical analysis in 32 cancer forms in the GSEA database facility. We have a mutation between 25 CBRGs. In The Cancer Genome Atlas database, clear cell renal cell carcinoma (ccRCC, n = 539) was upregulated or downregulated in 22 out of 25 cases (n = 72) compared with normal kidney tissue. Then, using LASSO regression analysis, the survival model that is based on nine risk-related CBRGs (CYP51A1, HMGCR, HMGCS1, IDI1, FDFT1, SQLE, ACAT2, FDPS, and NSDHL) is established. ROC curves confirmed the good omen of the new survival mode, and the area under the curve is 0.72 (5 years) and 0.709 (10 years). High SQLE and ACAT2 expression and low NSDHL, FDPS, CYP51A1, FDFT1, HMGCS1, HMGCR, and IDI1 expression were closely related to patients with high-risk renal clear cell carcinoma. Two types of Cox regression, uni- and multivariate, were used to determine risk scores, age, staging, and grade as independent risk factors for prognosis in patients with clear cell renal cell carcinoma. The results showed the prediction model established by 9 selected CBRGs could predict the prognosis more accurately.

Comparison of the Fatty Acid Metabolism Pathway in Pan-Renal Cell Carcinoma: Evidence from Bioinformatics.

This study analyzed and compared the potential role of fatty acid metabolism pathways in three subtypes of renal cell carcinoma. Biological pathways that were abnormally up- and downregulated were identified through gene set variation analysis in the subtypes. Abnormal downregulation of the fatty acid metabolism pathway occurred in all three renal cell carcinoma subtypes. Alteration of the fatty acid metabolism pathway was vital in the development of pan-renal cell carcinoma. Bioinformatics methods were used to obtain a panoramic view of copy number variation, single-nucleotide variation, mRNA expression, and the survival landscape of fatty acid metabolism pathway-related genes in pan-renal cell carcinoma. Most importantly, we used genes related to the fatty acid metabolism pathway to establish a prognostic-related risk model in the three subtypes of renal cell carcinoma. The data will be valuable for future clinical treatment and scientific research.

Bioorthogonal Phosphorogenic Rhenium(I) Polypyridine Sydnone Complexes for Specific Lysosome Labeling.

Invited for this month's cover is the group of Prof. Kenneth Kam-Wing Lo at City University of Hong Kong, Hong Kong, P. R. China. The cover picture shows the selective landing of a bioorthogonal spacecraft on a lysosomal planet modified with a strained cyclooctyne moiety in an intracellular environment with other organelles and a plethora of biomolecules. A sydnone moiety is appended to a luminescent rhenium(I) diimine unit as both an emission quencher and a bioorthogonal handle. Selective strain-promoted sydnone-alkyne cycloaddition (SPSAC) of the complex with a strained alkyne leads to impressive emission turn-on, which can be exploited in bioimaging and phototherapeutic applications. Read the full text of the article at 10.1002/cplu.202000029.

HFO-LADRC Lateral Motion Controller for Autonomous Road Sweeper.

How to make a controller robust and stable to reject the disturbance of uncertainty is an inevitable challenge. Aiming at addressing the lateral control problem for an autonomous road sweeper, a heading-error-based first order linear active disturbance rejective controller (HFO-LADRC) is proposed in this paper. To eliminate the lateral error and the heading error at the same time, a new model, called the heading-error-based model, is proposed for lateral motion, and the Lyapunov function was employed to explore the convergence ability of the heading error and lateral error. Since the heading-error-based model is first order, the ADRC is designed as first order and linear, and each module of the HFO-LADRC has been devised in detail. To ensure solution accuracy, the fourth order Runge-Kutta method was adopted as the differential system solver, and a typical ring scenario and a double lane-changing scenario were designed referencing the standard. Considering the obvious influence, wheelbase uncertainty, steering ratio uncertainty and Gaussian white noise disturbance were taken into account for the tests. The results illustrate that, in the case of both wheelbase uncertainty and steer ratio uncertainty, the HFO-LADRC has strong robustness and stability compared with a typical pure pursuit controller and classical SO-LADRC.