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Abstract Background Extensive biomedical studies have shown that clinical and environmental risk factors may not have sufficient predictive power for cancer prognosis. The development of high-throughput profiling technologies makes it possible to survey the whole genome and search for genomic markers with predictive power. Many existing studies assume the interchangeability of gene effects and ignore the coordination among them. Results We adopt the weighted co-expression network to describe the interplay among genes. Although there are several different ways of defining gene networks, the weighted co-expression network may be preferred because of its computational simplicity, satisfactory empirical performance, and because it does not demand additional biological experiments. For cancer prognosis studies with gene expression measurements, we propose a new marker selection method that can properly incorporate the network connectivity of genes. We analyze six prognosis studies on breast cancer and lymphoma. We find that the proposed approach can identify genes that are significantly different from those using alternatives. We search published literature and find that genes identified using the proposed approach are biologically meaningful. In addition, they have better prediction performance and reproducibility than genes identified using alternatives. Conclusions The network contains important information on the functionality of genes. Incorporating the network structure can improve cancer marker identification.

In the current study, an electronic nose (E-nose) and gas chromatography–ion mobility spectrometry (GC-IMS) were employed to investigate the volatile flavor compounds (VFCs) of intense flavor beef tallow (L) and ordinary beef tallow (P). The study results indicate that an E-nose combined with an LDA and GC-IMS combined with an OPLS-DA can effectively distinguish between the two types of beef tallow. Compared with ordinary beef tallow, the E-nose sensors of intense flavor beef tallow have stronger response signals to sulfides, terpenes, and nitrogen oxides. A total of 22 compounds contribute to making the flavor of intense flavor beef tallow more typical and richer; in contrast, ethyl acetate was the main aroma-active compound found in the ordinary beef tallow. Sulfur-containing compounds and terpenoids might be the key substances that cause sensory flavor differences between the two types of beef tallow. In conclusion, the results of this study clarify the characteristics and differences of the two types of beef tallow and provide an enhanced understanding of the differences in the flavors of the two types of beef tallow. [ABSTRACT FROM AUTHOR]

Background: In China, the basic insurance system consists of three schemes: the UEBMI (Urban Employee Basic Medical Insurance), URBMI (Urban Resident Basic Medical Insurance), and NCMS (New Cooperative Medical Scheme), across which significant differences have been observed. Since 2009, the central government has been experimenting with consolidating these schemes in selected areas. This study examines whether differences still exist across schemes after the consolidation. Methods: A survey was conducted in the city of Suzhou, collecting data on subjects 45 years old and above with at least one inpatient or outpatient treatment during a period of twelve months. Analysis on 583 subjects was performed comparing subjects’ characteristics across insurance schemes. A resampling-based method was applied to compute the predicted gross medical cost, OOP (out-of-pocket) cost, and insurance reimbursement rate. Results: Subjects under different insurance schemes differ in multiple aspects. For inpatient treatments, subjects under the URBMI have the highest observed and predicted gross and OOP costs, while those under the UEBMI have the lowest. For outpatient treatments, subjects under the UEBMI and URBMI have comparable costs, while those under the NCMS have much lower costs. Subjects under the NCMS also have a much lower reimbursement rate. Conclusions: Differences still exist across schemes in medical costs and insurance reimbursement rate post-consolidation. Further investigations are needed to identify the causes, and interventions are needed to eliminate such differences. [ABSTRACT FROM AUTHOR]

Background: Fatigue is a common source of distress for cancer survivors. The severity of cancer-related fatigue varies significantly, which may be due to individual differences in host factors., Aim: This cross-sectional study aims to explore how demographic, oncological, sociological, psychological, and stress-related hormones levels interact to influence the distinct experiences of fatigue (Cancer-related fatigue [CRF] occurrence and fatigue degree)., Methods: A cross-sectional study carried out at the oncology outpatient and ward department of Xiyuan Hospital of China Academy of Chinese Medical Sciences recruited 306 cancer patients between January 2021 to December 2021. General information, fatigue, psychological factors was evaluated by general information questionnaire, the Revised Piper's Fatigue Scale-Chinese Version (RPFS-CV), and the self-report Hospital Anxiety and Depression Scale (HADS). Stress-related hormones were measured with chemiluminescent enzyme immunoassay (Zhengzhou Antobio)., Results: 306 patients were included, 229 (74.8%) were diagnosed with CRF, including 94 (41.0%) with mild fatigue, 121 (52.8%) with moderate fatigue, and 14 (6.1%) with severe fatigue. Multivariate regression analysis showed that higher depression scores, aldosterone levels may increase the risk of CRF. Patients who are obese (Body mass index ≥ 28 kg/m 2 ) may help to reduce the risk of CRF. Other contributing factors for increased levels of fatigue ( p < 0.05) include being female, having anxiety, depression and high aldosterone levels., Conclusion: The research suggested that CRF was a common symptom in cancer survivors and pay attention to these influencing factors may help to better identify patients susceptible to fatigue and provide long-term, targeted interventions., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Gu, Xu, Zhu, Lam, Yi, Gong, Wang, Guo, Fu, Shi, Wang and Liu.)

Background: Extensive biomedical studies have shown that clinical and environmental risk factors may not have sufficient predictive power for cancer prognosis. The development of high-throughput profiling technologies makes it possible to survey the whole genome and search for genomic markers with predictive power. Many existing studies assume the interchangeability of gene effects and ignore the coordination among them., Results: We adopt the weighted co-expression network to describe the interplay among genes. Although there are several different ways of defining gene networks, the weighted co-expression network may be preferred because of its computational simplicity, satisfactory empirical performance, and because it does not demand additional biological experiments. For cancer prognosis studies with gene expression measurements, we propose a new marker selection method that can properly incorporate the network connectivity of genes. We analyze six prognosis studies on breast cancer and lymphoma. We find that the proposed approach can identify genes that are significantly different from those using alternatives. We search published literature and find that genes identified using the proposed approach are biologically meaningful. In addition, they have better prediction performance and reproducibility than genes identified using alternatives., Conclusions: The network contains important information on the functionality of genes. Incorporating the network structure can improve cancer marker identification.