Studying the mechanism underlying lipid metabolism in osteosarcoma based on transcriptomic RNA sequencing and single-cell data.

BACKGROUND: We aimed to provide a new typing method for osteosarcoma (OS) based on single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data from the perspective of lipid metabolism and examine its potential mechanisms in the onset and progression of OS. METHODS: Scores for six lipid metabolic pathways were calculated by single-sample gene set enrichment analysis (ssGSEA) based on a scRNA-seq dataset and three microarray expression profiles. Subsequently, cluster typing was conducted using unsupervised consistency clustering. Furthermore, single-cell clustering and dimensionality-reduction analyses identified cell subtypes. Finally, an analysis of cellular receptors was performed using CellphoneDB to identify cellular communication. RESULTS: OS was classified into three subtypes based on lipid metabolic pathways. Among them, patients in clust3 showed poor prognoses, whereas those in clust1 and clust2 exhibited good prognoses. In addition, ssGSEA analysis showed that patients in clust3 had lower immune cell scores. Moreover, the Th17 cell differentiation pathway was significantly differentially enriched between clust2 and clust3, with lower enrichment scores for metabolic pathways in the former relative to clust1 and clust2. In total, 24 genes were upregulated between clust1 and clust2, whereas 20 were downregulated in clust3. These observations were validated by single-cell data analysis. Finally, through scRNA-seq data analysis, we identified nine ligand-receptor pairs particularly critical for communication between normal and malignant cells. CONCLUSIONS: Three clusters were identified and the single-cell analysis revealed that malignant cells dominated lipid metabolism patterns in tumors, thereby influencing the tumor microenvironment.

Failure modes and effects analysis (FMEA) for the security of the supply chain system of the gas station in China.

With the popularity of automobiles, gas stations carry more gas supply and security risks. In order to effectively analyze the security of the supply chain system of the gas station, this study set the gas station as the center, then the upstream suppliers and downstream consumers were classified into three sub-systems, and the whole system was analyzed by using the method of failure modes and effects analysis (FMEA). A total of 50 typical cases of accidents at gas stations in China in the past 20 years have been collected from different websites, uses entropy weight method to deal with the cause of system failure modes, obtains and sorts the risk priority number (RPN). The type and failure cause of the most frequent accidents is the static electricity-induced explosion, and the effective measures to alleviate and deal with the accidents are put forward. The results of the study will help management and gas station staffs reasonably prevent gas station safety risks.

Construction of a novel mRNAsi-related risk model for predicting prognosis and immunotherapy response in osteosarcoma.

Background: Targeting cancer stem cells (CSC) may represent a future therapeutic direction for osteosarcoma (OS), which mainly relies on the identification of CSC markers. This study aimed to classify OS based on messenger ribonucleic acid (mRNA) stemness indices (mRNAsi) and construct a mRNAsi-related risk model to predict the prognosis of OS. Methods: The one-class logistic regression (OCLR) algorithm was applied to the RNA- sequencing (seq) data of human embryonic stem cells (hESC) and induced pluripotent stem cell (iPSC) lines to calculate mRNAsi. Weighted gene co-expression network analysis (WGCNA) was performed on data obtained from the TARGET database to screen the mRNAsi-related genes. Univariate Cox regression analysis was implemented to screen mRNAsi-related genes with prognostic significance for consensus clustering of OS. The least absolute shrinkage and selection operator (LASSO) and COX regression analysis were conducted to construct a risk model based on mRNAsi-related genes. Results: Six gene modules were identified in the TARGET database. The yellow module showed the strongest negative correlation with mRNAsi and the strongest significant positive correlation with the immune score and stromal score. OS was divided into three molecular subtypes with significant survival differences based on 73 mRNAsi-related genes with prognostic value for OS. The survival rate was ranked as C3 < C1 < C2 from low to high. The levels of immune components in C2 was significantly higher than those in C1 and C3. HSD11B2, GBP1, RNF130, APBB1IP, and NPC2 in the yellow module were used as variables for building the mRNAsi-related risk model. The survival rate of the high-risk group (as defined by this model) was significantly higher than that of the low-risk group, and it had significant survival prediction ability in 28 types of cancer. In addition, the mRNAsi-related risk model was superior to the Tumor Immune Dysfunction and Exclusion (TIDE) model in predicting the prognosis and immunotherapy response in all three immunotherapy cohorts. Conclusions: This study classified OS and constructed a mRNAsi-related risk model based on mRNAsi-related genes, which provides a potential tool for more accurate risk stratification of OS and prediction of immunotherapy response.

Developing a 5-Gene Signature Related to Pyroptosis for Osteosarcoma Patients.

Although the incidence of osteosarcoma (OS) is relatively low compared with other cancer types, the overall survival of metastatic OS was less than 30%. This study aimed to reveal the role of pyroptosis in osteosarcoma and develop a prognostic model related to pyroptosis. Weighted correlation network analysis (WGCNA) was applied to identify key gene modules related to pyroptosis. Univariate Cox regression analysis was used to screen prognostic genes related to pyroptosis. The least absolute shrinkage and selection operator (LASSO) and stepwise Akaike information criterion (stepAIC) were employed to optimize and construct a prognostic model. Five prognostic genes (COL13A1, TNFRSF1A, LILRA6, CTNNBIP1, and CD180) related to pyroptosis were identified. According to the 5-gene signature, OS samples were divided into high- and low-PPRS groups with differential prognosis. Immune-related pathways were more activated in the low-PPRS group. The 5-gene signature was effective and robust to predict OS prognosis. These five prognostic genes were involved in OS development and may serve as new targets for developing therapeutic drugs.

An Empirical Study on Hazardous Chemicals Risk of Urban Residents in China: Analysis of Mediating Effect and Channel Preference of Response Action Decision Model.

Because urban residents do not have a strong understanding of hazardous chemicals, they cannot effectively make response action decisions to ensure safety, protect lives, and reduce property damage. This paper constructs the Response Action Decision Model of hazardous chemicals, and analyzes the mediating effect of Information Processing and Threat Perception, as well as channel preferences of urban residents with different demographic characteristics. A total of 1700 questionnaires were collected in Chongqing, Tianjin, Fujian Zhangzhou, Shandong Zibo and Lanzhou, where there are significant hazardous chemicals factories. The results show that: Firstly, Information Processing and Threat Perception have significant mediating effects on the relationship between Mass Media, Social Media, Face-to-face communication and Response Action Decision in a single channel, which can effectively promote the spread effect of different channels, affecting the ways that urban residents make hazard response action decisions; secondly, Information Processing and Threat Perception do not have a mediating effect on the relationship between the channel combination of "Mass Media ↔ Social Media", "Mass Media ↔ Face-to-face communication", "Social Media ↔ Face-to-face communication" and Response Action Decision, and the channel combination can directly link to the Response Action Decision; thirdly, in terms of the extent that it affects urban residents to make response action decisions, Mass Media is greater than Social Media and greater than Face-to-face communication; fourthly, two demographic characteristics of gender and experience have a stronger moderating effect for the Mass Media channel, while other demographic characteristics have greater influences on the Response Action Decision Model; finally, the Response Action Decision Model can be better applied to those analyses and research which address threat perception of hazardous chemicals and response action decisions of urban residents in China.

A Recurrent Synovial Osteochondromatosis of the Knee: A Case Report.

We report a case of a farmer who presented with synovial osteochondromatosis of his right knee that mimicked a huge hardball. A synovial proliferative disease associated with metaplasia of cartilage resulting in sporadic multiple intra-articular and extra-articular loose bodies. Our focus is to report a rare case successfully operated which has an educational significance in clinical practice.

Racing Crystallization Mechanism for Economical Design of Single-Crystal Hollow ZSM-5 with the Broken Limit of Si/Al Ratio and Improved Mass Transfer.

Development of economic strategy to synthesize hollow zeolite with widely tunable Si/Al ratios providing variable acidity is of great significance in industry. Here, a one-step and low-cost strategy without mesoporogen was successfully developed to synthesize single-crystal hollow ZSM-5 containing mesopores/macropores, with variable Si/Al ratios of about 14-∞ and 114-∞ at critical TPA+/SiO2 ratios of 0.05-0.1 and 0.05, respectively. This is the first time the usage of a large amount of TPAOH was avoided while breaking the traditional limitation of Si/Al ratio (25-50). The component of synthesis system and crystallization temperature acting as the vital roles in hollow structure has been confirmed by a series of characterization. Moreover, according to the investigation of the evolution process, a novel racing crystallization mechanism based on the competition relationship between surface crystallization and the internal dissolution rate was proposed for the first time. The racing crystallization mechanism and internal nonprotective aluminum become the crucial factors for synthesis. The prepared hollow ZSM-5 zeolites exhibit superior catalytic performance in the different acidity-catalyzed condensation involving large molecules between benzaldehyde and n-butyl alcohol as well as 2-hydroxyacetophenone, which is mainly attributed to the property acidity, more accessible active Al sites on the surface, and shorter diffusion path. By calculating, the effectiveness factor (η) of hollow zeolite is close to 1, further confirming its better mass transfer ability. The strategy has also been successfully extended to the synthesis of high-amount Fe-doped, Ga-doped, and B-doped hollow silicate-1.

Signature based on metabolic-related gene pairs can predict overall survival of osteosarcoma patients.

BACKGROUND: Osteosarcoma is a tumour of malignant origin in children and adolescents. Recent progression indicates that it is necessary to develop new therapies to improve the patient's prognosis rather than strengthen anti-tumour chemotherapy. Researchers recently realised that cancer is a kind of disease with a metabolic disorder, and metabolic reprogramming is becoming a new cancer hallmark. Hence, our study's primary purpose is to explore the value of genes related to osteosarcoma metabolism. METHODS: From public databases, three osteosarcoma datasets with adequate clinical information were obtained. Besides, the IMvigor dataset through the 'IMvigor' package as a supplement was downloaded, the metabolic-related genes were identified, and these genes were used to construct the metabolic-related gene pairs (MRGP). Based on the prognosis-related MRGP, two molecular subtypes were identified. There are significant differences in the metabolic characteristics between the two molecular subtypes. Subsequently, the MRGP signature is constructed using the least absolute shrinkage and selection operator regression method. Finally, use SubMap analysis to evaluate the response of patients in the MRPG signature group to immunotherapy. RESULTS: The MRGP signature can reliably predict overall survival in patients with osteosarcoma. The MRGP signature is also associated with osteosarcoma patients' metastatic status and can be used for subsequent risk classification of metastatic patients. The immunotherapy is more likely to benefit the patients in the MRGP low-risk group. CONCLUSION: Metabolic-related gene pairs signature can assess the prognosis of patients with osteosarcoma.

Molecular analysis of grass carp reovirus HZ08 genome segments 1-3 and 5-6.

A new grass carp reovirus, assigned HZ08, was isolated from a diseased grass carp case during routine examination in Huzhou City, Zhejiang Province, China. The complete nucleotide sequences of genomic segments S1-S3 and S5-S6 were obtained and comprised 3927, 3870, 3753, 2229, and 2030 bp, respectively. Each segment contained a single open reading frame which encoded putative proteins of 143.6, 143.1, 135.9, 80.5, and 68.4 kDa, respectively. Conserved motifs 5' (GUAAUUU...UUCAUC) 3' were found at the ends of each segment. At the amino acid level, HZ08 S1-S3 and S5-S6 showed similarity to the corresponding segments of Aquareovirus. Further phylogenetic analysis using the amino acid sequences of the RNA-dependent RNA polymerases protein encoded by S2 revealed that HZ08 formed a cluster close to the aquareovirus, but was far from the other isolates, which indicated that HZ08 is likely to be a new member of Aquareovirus.

Construction of immune-related gene pairs signature to predict the overall survival of osteosarcoma patients.

The purpose of this study is to establish the prognosis of osteosarcoma patients based on the characteristics of immune-related gene pairs. We used the lasso Cox regression model to construct and verify the signature consisting of 14 immune-related gene pairs. This signature can accurately predict the overall survival of osteosarcoma patients and is an independent prognostic factor for osteosarcoma patients. For this we constructed a signature-based nomogram. The results of the nomogram show that our signature can bring clinical net benefits. We then assessed the abundance of infiltrating immune cells in each sample, and combine the results of the gene set enrichment analysis of a single sample to explore the differences in the immune microenvironment between IRPG signature groups. The result of gene set enrichment analysis shows the strong relationship between signature and immune system. Finally, we evaluated the relationship between signature and immunotherapy efficiency using algorithms such as TIMI and SubMap to explore patients who might benefit from immunotherapy. In conclusion, our signature can predict the overall survival rate of osteosarcoma patients and provide potential guidance for exploring patients who may benefit from immunotherapy.

MACC1 Contributes to the Development of Osteosarcoma Through Regulation of the HGF/c-Met Pathway and Microtubule Stability.

Osteosarcoma (OS) is the most prevalent human bone malignancy, and presents a global annual morbidity of approximately five cases per million. Notably, precise and efficient targeted therapy has become the most promising strategy for the treatment of OS; however, there is still an urgent need for the identification of suitable therapeutic targets. Metastasis-associated in colon cancer 1 (MACC1) was first identified in colon tumors by differential display RT-PCR, and was shown to be involved in the regulation of colon tumor growth and metastasis through the hepatocyte growth factor (HGF)/c-Met signaling pathway. Additionally, MACC1 overexpression has been reported to induce the growth of several types of cancers, including glioblastoma multiforme and gastric cancer. However, whether MACC1 also plays a role in the progression of OS remains unclear. In this study, we found that MACC1 was highly expressed in human OS tissues, as well as in U-2OS and MG-63 cells, when compared with normal tissues and osteoblasts, respectively. Our data further indicated that MACC1 expression was correlated with several clinicopathological features of OS. Through in vitro assays, we found that MACC1 depletion markedly suppressed the proliferative ability of both OS cells and endothelial cells, and inhibited the angiogenic capacity of endothelial cells. Similarly, MACC1 depletion inhibited tumor growth, metastasis, and angiogenesis in mice. Mechanistically, we found that MACC1 could bind to the MET promoter, and enhanced the proliferation of both OS cells and endothelial cells through the HGF/c-Met signaling pathway. Furthermore, we show that MACC1 also promoted angiogenesis by regulating microtubule dynamics, thereby promoting the progression of OS. Our results indicate that MACC1 may be a new and promising therapeutic target for the treatment of OS.

Meta-Analysis of Hematological Biomarkers as Reliable Indicators of Soft Tissue Sarcoma Prognosis.

Background: Several recent studies have reported the reliable prognostic effect of hematological biomarkers in various tumors. Yet, the prognostic value of these hematological markers in soft tissue sarcoma (STS) remains inconclusive. Thus, the aim of this meta-analysis was to check the effect of hematological markers on the prognosis of STS. Methods: We systematically searched for relevant papers published before October 2019 in the PubMed and EMBASE databases. Overall survival (OS) and disease-specific survival (DSS) were the primary outcome, whereas disease-free survival was the secondary outcome. A thorough study of hazard ratios (HR) and 95% of confidence intervals (CIs) was done for determining the prognostic significance. Results: We performed 23 studies that comprised of 4,480 patients with STS. The results revealed that higher neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP), and platelet-to-lymphocyte ratio (PLR) were associated with poor OS/DFS (HR = 2.08/1.72, for NLR; HR = 1.92/1.75, for CRP, and HR = 1.86/1.61, for PLR). In contrast, a low lymphocyte-to-monocyte ratio (LMR) was relate to worse OS/DFS (HR = 2.01/1.90, for LMR). Moreover, pooled analysis illustrated that elevated NLR and CRP represents poor DSS, with HRs of 1.46 and 2.06, respectively. In addition, combined analysis revealed that higher Glasgow prognostic score (GPS) was linked to an adverse OS/DSS (HR = 2.35/2.77). Conclusion: Our meta-analysis suggested that hematological markers (NLR, CRP, PLR, LMR, and GPS) are one of the important prognostic indicators for patients affected by high-grade STS and patients with the STS being located in the extremity.

Cause Analysis of Unsafe Behaviors in Hazardous Chemical Accidents: Combined with HFACs and Bayesian Network.

Hazardous chemical accidents (HCAs) seriously endanger public life, property, and health. Human and organizational factors are important causes of many kinds of accidents. In order to systematically explore the influencing factors of unsafe behaviors in HCAs in China, the method of human factors analysis and classification system based on the Bayesian network (BN-HFACs) was introduced. According to the 39 investigation reports of HCAs in China, the origin Bayesian network (BN) was obtained and the failure sensitivity of every node in BN was calculated. The results have shown that hazardous material environment (1.63) and mechanical equipment (0.49) in the level of preconditions of unsafe behavior have the same direction failure effect with operation error, while there is no factor has the same direction failure effect with operation violate. Some factors in organization influence and unsafe supervision, such as organization climate (0.34), operation guidance (0.37), planned operation (0.22), and legal supervision (0.19), are also important reasons for operational errors, while resource management (0.12), hidden investigation (0.18) and legal supervision (0.13) have an impact on operation violates. Moreover, there are still close relationships between other hierarchical elements, such as the operation guidance effect on the hazardous material environment (6.60), and the organizational climate has the most obvious impact on other factors at the level of organizational factors. Based on the above research conclusions, suggestions for individual, enterprise, and government were put forward, respectively, and the limitations of this study were also clarified.

Progressive visualization of losslessly compressed DICOM files over the Internet.

Presented in this paper is a method for progressive transfer and visualization of losslessly compressed DICOM files. The files from the same study are considered as a volumetric object, which is progressively compressed using a quadtree-based method. The textual information of the DICOM file is compressed using a predicting scheme. Decompression and visualization are implemented with Java applet technology. Users can display and interact with the object even during the data transfer. Tests have shown that an object can be recognized up to 70% faster than with the classical approaches.

Beyond pairwise strategy updating in the prisoner's dilemma game.

In spatial games players typically alter their strategy by imitating the most successful or one randomly selected neighbor. Since a single neighbor is taken as reference, the information stemming from other neighbors is neglected, which begets the consideration of alternative, possibly more realistic approaches. Here we show that strategy changes inspired not only by the performance of individual neighbors but rather by entire neighborhoods introduce a qualitatively different evolutionary dynamics that is able to support the stable existence of very small cooperative clusters. This leads to phase diagrams that differ significantly from those obtained by means of pairwise strategy updating. In particular, the survivability of cooperators is possible even by high temptations to defect and over a much wider uncertainty range. We support the simulation results by means of pair approximations and analysis of spatial patterns, which jointly highlight the importance of local information for the resolution of social dilemmas.

Win-stay-lose-learn promotes cooperation in the spatial prisoner's dilemma game.

Holding on to one's strategy is natural and common if the later warrants success and satisfaction. This goes against widespread simulation practices of evolutionary games, where players frequently consider changing their strategy even though their payoffs may be marginally different than those of the other players. Inspired by this observation, we introduce an aspiration-based win-stay-lose-learn strategy updating rule into the spatial prisoner's dilemma game. The rule is simple and intuitive, foreseeing strategy changes only by dissatisfied players, who then attempt to adopt the strategy of one of their nearest neighbors, while the strategies of satisfied players are not subject to change. We find that the proposed win-stay-lose-learn rule promotes the evolution of cooperation, and it does so very robustly and independently of the initial conditions. In fact, we show that even a minute initial fraction of cooperators may be sufficient to eventually secure a highly cooperative final state. In addition to extensive simulation results that support our conclusions, we also present results obtained by means of the pair approximation of the studied game. Our findings continue the success story of related win-stay strategy updating rules, and by doing so reveal new ways of resolving the prisoner's dilemma.

Adaptive and bounded investment returns promote cooperation in spatial public goods games.

The public goods game is one of the most famous models for studying the evolution of cooperation in sizable groups. The multiplication factor in this game can characterize the investment return from the public good, which may be variable depending on the interactive environment in realistic situations. Instead of using the same universal value, here we consider that the multiplication factor in each group is updated based on the differences between the local and global interactive environments in the spatial public goods game, but meanwhile limited to within a certain range. We find that the adaptive and bounded investment returns can significantly promote cooperation. In particular, full cooperation can be achieved for high feedback strength when appropriate limitation is set for the investment return. Also, we show that the fraction of cooperators in the whole population can become larger if the lower and upper limits of the multiplication factor are increased. Furthermore, in comparison to the traditionally spatial public goods game where the multiplication factor in each group is identical and fixed, we find that cooperation can be better promoted if the multiplication factor is constrained to adjust between one and the group size in our model. Our results highlight the importance of the locally adaptive and bounded investment returns for the emergence and dominance of cooperative behavior in structured populations.