The role of cattle manure-driven polysaccharide precursors in humus formation during composting of spent mushroom substrate.

The study examined the impact of adding cattle manure to the composting process of Agaricus bisporus mushroom substrate on compost humification. A control group CK comprised entirely of Agaricus bisporus mushroom substrate, while the experimental group CD (70 percent Agaricus bisporus mushroom substrate and 30 percent cattle manure) comprised the two composting treatments that were established. The study determined that the addition of cow dung has promoted the formation of humus components. Particularly, humic substance (HS-C) and humic acid (HA) increased by 41.3 and 74.7%, respectively, and the ratio of humic acid to fulvic acid (HA/FA) also increased by 2.78. It showed that the addition of cow dung accelerated the synthesis and decomposition of precursors, such as polysaccharides, polyphenols, and reducing sugars. Thereby promoting the formation of humic acid. Network analysis revealed that adding cow dung promoted microbial interactions increased the complexity and stability of the bacterial and fungal symbiotic network, enhanced cooperation and reciprocity among microbes, and assisted in transforming fulvic acid (FA) components. Structural equation modeling (SEM) is a multivariate data analysis method for analyzing complex relationships among constructs and core indicators. SEM illustrated that introducing cattle manure into the composting process resulted in alterations to the correlation between physicochemical parameters and the microbial community, in addition to humus formation. Polysaccharides are the primary precursors for polymerization to form HA, which is an essential prerequisite for the conversion of fulvic acid to humic acid. Additionally, microbes affected the formation of humus, with bacteria substantially more influential than fungi. These findings provide new ideas for regulating the degree of humification in the composting process and have important practical implications for optimizing mushroom cultivation and composting techniques today.

Construction of an adverse outcome pathway framework for arsenic-induced lung cancer using a network-based approach.

Environmental pollutants are considered as a cause of tumorigenesis, but approaches to assess their risk of causing tumors remain insufficient. As an alternative approach, the adverse outcome pathway (AOP) framework is used to assess the risk of tumors caused by environmental pollutants. Arsenic is a pollutant associated with lung cancer, but early assessment of lung cancer risk is lacking. Therefore, we applied the AOP framework to arsenic-induced lung cancer. A systematic review revealed increased risks of lung cancer following exposure to a range of arsenic concentrations in drinking water (OR = 1.83, 95 % CI = 1.46-2.30). We obtained, from public databases, genes related to risk of arsenic-induced lung cancer. Then, Cox and LASSO regressions were used to screen target genes from the risk genes. Subsequently, target genes, phenotypes, and pathways were used to construct the computational AOP network, which was determined by Cytoscape to have 156 edges and 45 nodes. Further, target genes, phenotypes, and pathways were used as molecular initiating events and key events to construct the AOP framework depending on upstream and downstream relationships. In the AOP framework, by Weight of Evidence, arsenic exposure increased levels of EGFR, activated the PI3K/AKT pathway, regulated cell proliferation by promoting the G1/S phase transition, and caused generation of lung cancers. External validation was achieved through arsenite-induced, malignant transformed human bronchial epithelial (HBE) cells. Overall, these results, by integration into existing data to construct an AOP framework, provide insights into the assessment of lung cancer risk for arsenic exposure. Special attention needs to be focused on populations with low-dose arsenic exposure.

miR-21-Mediated Endothelial Senescence and Dysfunction Are Involved in Cigarette Smoke-Induced Pulmonary Hypertension through Activation of PI3K/AKT/mTOR Signaling.

Smoking is a pathogenic factor for pulmonary hypertension (PH). Our previous study showed that serum miR-21 levels are elevated in smokers. miR-21 is considered as engaged in the PH process; however, its mechanisms remain unclear. In this investigation, we found that in the lung tissue of smoking-induced PH patients, the levels of miR-21 and aging markers (p21 and p16) were upregulated, and the function of pulmonary vascular endothelial cells was also impaired. Exposure of mice to cigarette smoke (CS) for four months caused similar changes in lung tissues and increased pulmonary arterial pressure, which were attenuated by knockout of miR-21. Further, human umbilical vein endothelial cells (HUVECs) exposed to cigarette smoke extract (CSE) revealed upregulation of miR-21 levels, depression of PTEN, activation of PI3K/AKT/mTOR signaling, an increase in senescence indexes, and enhanced dysfunction. Inhibiting miR-21 overexpression reversed the PTEN-mTOR signaling pathway and prevented senescence and dysfunction of HUVECs. In sum, our data indicate that miR-21-mediated endothelial senescence and dysfunction are involved in CS-induced PH through the activation of PI3K/AKT/mTOR signaling, which suggests that selective miR-21 inhibition offers the potential to attenuate PH.

Deubiquitination of CDC6 by OTUD6A promotes tumour progression and chemoresistance.

BACKGROUND: CDC6 is an oncogenic protein whose expression level fluctuates during the cell cycle. Although several E3 ubiquitin ligases responsible for the ubiquitin-mediated proteolysis of CDC6 have been identified, the deubiquitination pathway for CDC6 has not been investigated. METHODS: The proteome-wide deubiquitinase (DUB) screening was used to identify the potential regulator of CDC6. Immunofluorescence, protein half-life and deubiquitination assays were performed to determine the protein stability of CDC6. Gain- and loss-of-function experiments were implemented to analyse the impacts of OUTD6A-CDC6 axis on tumour growth and chemosensitivity in vitro. N-butyl-N-(4-hydroxybutyl) nitrosamine (BBN)-induced conditional Otud6a knockout (CKO) mouse model and tumour xenograft model were performed to analyse the role of OTUD6A-CDC6 axis in vivo. Tissue specimens were used to determine the association between OTUD6A and CDC6. RESULTS: OTUD6A interacts with, depolyubiquitinates and stabilizes CDC6 by removing K6-, K33-, and K48-linked polyubiquitination. Moreover, OTUD6A promotes cell proliferation and decreases sensitivity to chemotherapy by upregulating CDC6. CKO mice are less prone to BCa tumorigenesis induced by BBN, and knockdown of OTUD6A inhibits tumour progression in vivo. Furthermore, OTUD6A protein level has a positive correlation with CDC6 protein level, and high protein levels of OTUD6A and CDC6 are associated with poor prognosis in patients with bladder cancer. CONCLUSIONS: We reveal an important yet missing piece of novel DUB governing CDC6 stability. In addition, our findings propose a model for the OTUD6A-CDC6 axis that provides novel insights into cell cycle and chemosensitivity regulation, which may become a potential biomarker and promising drug target for cancer treatment.

NSUN2 promotes lung adenocarcinoma progression through stabilizing PIK3R2 mRNA in an m5C-dependent manner.

It is well known that 5-methylcytosine (m5C) is involved in variety of crucial biological processes in cancers. However, its biological roles in lung adenocarcinoma (LAUD) remain to be determined. The LUAD samples were used to assess the clinical value of NOP2/Sun RNA Methyltransferase 2 (NSUN2). Dot blot was used to determine global m5C levels. ChIP and dual-luciferase assays were performed to investigate the MYC-associated zinc finger protein (MAZ)-binding sites in NSUN2 promoter. RNA-seq was used to explore the downstream molecular mechanisms of NSUN2. Dual luciferase reporter assay, m5C-RIP-qPCR, and mRNA stability assay were conducted to explore the effect of NSUN2-depletion on target genes. Cell viability, transwell, and xenograft mouse model were designed to demonstrate the characteristic of NSUN2 in promoting LUAD progression. The m5C methyltransferase NSUN2 was highly expressed and caused elevated m5C methylation in LUAD samples. Mechanistically, MAZ positively regulated the transcription of NSUN2 and was related to poor survival of LUAD patients. Silencing NSUN2 decreased the global m5C levels, suppressed proliferation, migration and invasion, and inhibited activation of PI3K-AKT signaling in A549 and SPAC-1 cells. Phosphoinositide-3-Kinase Regulatory Subunit 2 (PIK3R2) was upregulated by NSUN2-mediated m5C methylation by enhancing its mRNA stabilization and activated the phosphorylation of the PI3K-AKT signaling. The present study explored the underlying mechanism and biological function of NSUN2-meditated m5C RNA methylation in LUAD. NSUN2 was discovered to facilitate the malignancy progression of LUAD through regulating m5C modifications to stabilize PIK3R2 activating the PI3K-AKT signaling, suggesting that NSUN2 could be a novel biomarker and promising therapeutic target for LUAD patients.

CUL4B functions as a tumor suppressor in KRAS-driven lung tumors by inhibiting the recruitment of myeloid-derived suppressor cells.

Lung cancer is the leading cause of cancer-related death worldwide. KRAS mutations are the most common oncogenic alterations found in lung cancer. Unfortunately, treating KRAS-mutant lung adenocarcinoma (ADC) remains a major oncotherapeutic challenge. Here, we used both autochthonous and transplantable KRAS-mutant tumor models to investigate the role of tumor-derived CUL4B in KRAS-driven lung cancers. We showed that knockout or knockdown of CUL4B promotes lung ADC growth and progression in both models. Mechanistically, CUL4B directly binds to the promoter of Cxcl2 and epigenetically represses its transcription. CUL4B deletion increases the expression of CXCL2, which binds to CXCR2 on myeloid-derived suppressor cells (MDSCs) and promotes their migration to the tumor microenvironment. Targeting of MDSCs significantly delayed the growth of CUL4B knockdown KRAS-mutant tumors. Collectively, our study provides mechanistic insights into the novel tumor suppressor-like functions of CUL4B in regulating KRAS-driven lung tumor development.

Dynamic Covalent Dextran Hydrogels as Injectable, Self-Adjuvating Peptide Vaccine Depots.

Dextran-based hydrogels are promising therapeutic materials for drug delivery, tissue regeneration devices, and cell therapy vectors, due to their high biocompatibility, along with their ability to protect and release active therapeutic agents. This report describes the synthesis, characterization, and application of a new dynamic covalent dextran hydrogel as an injectable depot for peptide vaccines. Dynamic covalent crosslinks based on double Michael addition of thiols to alkynones impart the dextran hydrogel with shear-thinning and self-healing capabilities, enabling hydrogel injection. These injectable, non-toxic hydrogels show adjuvant potential and have predictable sub-millimolar loading and release of the peptide antigen SIINFEKL, which after its release is able to activate T-cells, demonstrating that the hydrogels deliver peptides without modifying their immunogenicity. This work demonstrates the potential of dynamic covalent dextran hydrogels as a sustained-release material for the delivery of peptide vaccines.

Machine-learning-based approach for predicting postoperative skeletal changes for orthognathic surgical planning.

BACKGROUND: Manually surgical planning becomes an increasing workload of surgeons because of the fast-growing patient population. This study introduced a machine-learning-based approach to assist surgical planning in orthognathic surgery. METHODS: Both preoperative and one-year-later postoperative computerised tomography images of 56 patients were collected. A 12-layers cascaded deep neural network structure with two successive models was proposed to yield an end-to-end solution, where the first model extracts landmarks from 2D patches of 3D volume and the second model predicts postoperative skeletal changes. RESULTS: The experimental results showed that the model obtained a prediction accuracy of 5.4 mm at the landmark level in 42.9 s. It also represented 74.4% of 3D regions at volume level when compared with the ground truth of human surgeons. CONCLUSIONS: This study demonstrated the feasibility of predicting postoperative skeletal changes for orthognathic surgical planning by using machine learning, showing great potential for reducing the workload of surgeons.

Automatic 3D landmarking model using patch-based deep neural networks for CT image of oral and maxillofacial surgery.

BACKGROUND: Manual landmarking is a time consuming and highly professional work. Although some algorithm-based landmarking methods have been proposed, they lack flexibility and may be susceptible to data diversity. METHODS: The CT images from 66 patients who underwent oral and maxillofacial surgery (OMS) were landmarked manually in MIMICS. Then the CT slices were exported as images for recreating the 3D volume. The coordinate data of landmarks were further processed in Matlab using a principal component analysis (PCA) method. A patch-based deep neural network model with a three-layer convolutional neural network (CNN) was trained to obtain landmarks from CT images. RESULTS: The evaluating experiment showed that this CNN model could automatically finish landmarking in an average processing time of 37.871 seconds with an average accuracy of 5.785 mm. CONCLUSION: This study shows a promising potential to relieve the workload of the surgeon and reduces the dependence on human experience for OMS landmarking.

Cumulative sum analysis of the learning curve for the preclosure technique using Proglide.

OBJECTIVES: Our study aims to assess the technical quality and the learning curve of the preclosure technique for a vascular surgeon using Proglide using cumulative sum analysis (CUSUM analysis). METHODS: This study was designed retrospectively and enrolled 81 consecutive patients with 88 access sites who underwent endovascular aortic repair or thoracic endovascular aortic repair with the preclosure technique using Proglide between July 2017 and February 2018. The patients were divided into 2 groups chronologically: (A) the first 40 cases and (B) the latter 41 cases. Logistic regression analysis was used to assess the impact of technical risk factors on the success of the preclosure technique, and the χ2 test and 1-way ANOVA were applied to analyse the distribution of individual characteristics and risk factors between the 2 groups. CUSUM analysis was adapted to analyse the learning curve and to monitor the technical quality, with a predetermined target failure rate of 5%, an alternative failure rate of 20% and calculated 80% 'alert', 95% 'alarm' and 80% 'reassurance' lines. RESULTS: Primary technical success was obtained in 81 (92.05%) access sites. There were no significant correlations between primary technical success and risk factors, including, common femoral artery diameter (P = 0.88), common femoral artery depth from the skin (P =0.94), the level of common femoral artery calcification (P =0.86) and size of sheath (P =0.96). Moreover, the distribution of related risk factors was not significantly different between groups A and B. CUSUM analysis showed that the cumulative failure rate never crossed the 80% 'alert' and 95% 'alarm' lines. Additionally, the failure rate began to approach the 80% 'reassurance' line after ∼22 cases and crossed the 80% 'reassurance' line after 36 cases. CONCLUSIONS: The technique of totally percutaneous access using Proglide is safe and effective for an experienced vascular surgeon, even if the operator has no previous experience with any preclosure techniques. CUSUM analysis showed that 36 cases are necessary to achieve the target failure rate of 5%.