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Objective To investigate the clinicopathological significance of PDC in liver metastases and analyze the correlation of PDC between liver metastases and primary lesions. Methods Retrospective analysis of 72 matched cases of colorectal cancer with liver metastases was performed. The PDC in primary tumor and liver metastatic lesion was interpreted synchronously, and then the relationship between PDC in liver metastasis and clinicopathological parameters was analyzed based on the correlation of PDC between primary and metastatic lesions. In addition, PDC were interpreted in accordance with Uenos' standard. Results Among the 72 cases of liver metastasis of colorectal cancer, the number of G1, G2, and G3 graded by PDC was 28, 24, and 20, respectively. The PDC in liver metastatic lesion was correlated with tumor budding in liver metastatic lesion and PDC grade of primary lesion. No significant correlation with the size and number of liver metastatic lesion, the site, WHO grade, depth of invasion, lymph node metastasis, vascular invasion or tumor budding of the primary lesion was observed. Conclusion A positive correlation is found between liver metastasis of colorectal adenocarcinoma and PDC grade of primary tumor. Evaluating the PDC grade of primary tumor may provide a reference for the risk of liver metastasis.

Background and purpose: Histological grading based on the degree of differentiation has limitations in evaluating the biological behavior of colorectal cancer. Finding more morphological indicators will provide more evidence for the prognosis and stratified management of colorectal cancer. This study aimed to investigate the relationship between poorly differentiated clusters (PDC) and clinicopathological parameters in colorectal adenocarcinoma and its significance. Methods: Data of 101 patients with colorectal adenocarcinoma who underwent radical surgical resection in Zhuhai Hospital of Guangdong Provincial Hospital of Traditional Chinese Medicine from January 2019 to October 2020 were collected. Among them, there were 54 males and 47 females, ranging in age from 29 to 86 years with median age of 62 years. Tumor size ranged from 1.5 to 9.0 cm (mean 4.5 cm). There were 42 cases of left colon cancer, 21 cases of right colon cancer and 38 cases of rectal cancer. The number of PDC of colorectal adenocarcinoma in H-E section was observed under light microscope and graded, and the relationship between PDC grade and other clinicopathological parameters of colorectal adenocarcinoma was analyzed. Results: Among 101 cases of colorectal adenocarcinoma, 42 cases (41.6%) were G1 grade, 29 cases (28.7%) were G2 grade, and 30 cases (29.7%) were G3 grade. In colorectal adenocarcinoma, PDC was positively correlated with histological grade, invasion depth, lymph node metastasis, lymphovascular invasion, nerve invasion, distant metastasis stage and tumor budding (TB) (P ＜ 0.05), but not with patient age, gender, tumor site or tumor size (P ＞ 0.05). Conclusion: PDC is closely related to the invasive biological behavior of colorectal adenocarcinoma. PDC is likely to be a more effective prognostic marker than traditional histological grading after TB. Identification and evaluation of PDC grading in colorectal adenocarcinoma can better predict the biological behavior of colorectal adenocarcinoma, and thus more accurately guide the treatment and prognosis evaluation of colorectal cancer.

A streaming graph is a constantly growing sequence of edges, which forms a dynamic graph that changes with every edge in the stream. An anomalous behavior in a streaming graph can be modeled as an edge or a subgraph that is unusual compared to the rest of the graph. Identifying anomalous behaviors in real time is essential to the early warning of abnormal or notable events. Due to the complexity of the problem, little work has been reported so far to solve the problem. In this paper, we propose Finger-based Higher-order Graph Sketch (FHGS for short), which is an approximate data structure for streaming graphs with linear memory usage, high update speed, and high accuracy and supports both edge and subgraph anomaly detection. FHGS first maps each edge into a matrix based on hash functions, and then counts its frequency in a time window with unique fingerprints for detecting anomalies. Extensive experiments confirm that our approach generate high-quality results compared to baseline methods. [ABSTRACT FROM AUTHOR]

Gas boilers exhibit thermal inefficiency and unsatisfying pollutant emissions. In this study, numerical simulations were conducted to examine the effect of humidified oxygen-enriched air on methane combustion in a furnace and the effects of different premixed ratios of air on the temperature field inside the furnace, intermediate product OH groups, component concentration distribution, and pollutants. Although humidification of ambient air effectively reduced the flame center temperature and mass concentration of the NOx generated during combustion in the furnace, the highest growth rate of CO concentration at the furnace outlet was 18.6%. Humidification of oxygen-enriched air increased the center temperature and outlet NO concentration of the furnace compared with those during no oxygen enrichment, but the outlet CO concentration showed a decreasing trend, with the highest decrease rate of 34.6%. This study determined an optimal CO–air premix ratio with a moisture concentration of 50 g/kg dry air and an oxygen concentration of 23%. The air humidification and oxygen enrichment technology proposed in this article provides a technical reference for low nitrogen transformation of existing gas boilers. [ABSTRACT FROM AUTHOR]

Desorption of activated carbon saturated with VOCs (volatile organic compounds) under supercritical CO2 is considered to be a promising method, but the desorption ratio is greatly affected by operating parameters, and the influence mechanism is still ambiguous. In this paper, the influence mechanism of pressure which is the most important operating parameter on the desorption ratio is studied. Toluene is considered as the representative of VOC, the relationship between toluene desorption ratio and pressure is investigated by experimental methods, the diffusion of supercritical CO2 molecules in the nano pores of activated carbon and the interaction between CO2 molecules and toluene molecules are investigated by molecular dynamics simulation. The results show that increasing pressure enhances the interaction energy between CO2 and toluene, which enhances the desorption driving force of toluene. Meanwhile, increasing pressure also reduces the adsorption between activated carbon and toluene, this reduces the desorption resistance of toluene. Finally, the toluene desorption ratio increases as pressure increases. [ABSTRACT FROM AUTHOR]

Inferring the topology of a network from network dynamics is a significant problem with both theoretical research significance and practical value. This paper considers how to reconstruct the network topology according to the continuous-time data on the network. Inspired by the generative adversarial network(GAN), we design a deep learning framework based on network continuous-time data. The framework predicts the edge connection probability between network nodes by learning the correlation between network node state vectors. To verify the accuracy and adaptability of our method, we conducted extensive experiments on scale-free networks and small-world networks at different network scales using three different dynamics: heat diffusion dynamics, mutualistic interaction dynamics, and gene regulation dynamics. Experimental results show that our method significantly outperforms the other five traditional correlation indices, which demonstrates that our method can reconstruct the topology of different scale networks well under different network dynamics. [ABSTRACT FROM AUTHOR]

The desorption of activated carbon saturated with VOCs (volatile organic compounds) may not only prolong the life of activated carbon, but also promote environmental protection. Supercritical CO2 is considered to be a promising desorption method because it may avoid the inherent defects of traditional thermal methods. However, the desorption mechanism still remains unclear because the desorption process in the nanopores cannot be observed by the macro-experiments. In this paper, toluene is considered the representative of VOC; the diffusion of CO2, the interaction between CO2 and toluene, and the diffusion of toluene in the nanopore of activated carbon are studied using molecular dynamics simulation. The research results at the molecular level reveal that the strong diffusion of CO2, the interaction energy between CO2 and toluene, and CO2 greatly improving the mobility of toluene play decisive roles for the desorption mechanism. The research results of this paper may provide some beneficial guides for further studying the influence mechanism of VOC types and operating parameters on VOC desorption behavior under supercritical CO2. [ABSTRACT FROM AUTHOR]