In this study, 4,7-dimethoxy-5-methyl-l,3-benzodioxole (SY-1) was isolated from three different sources of dried fruiting bodies of Antrodia camphorate (AC). AC is a medicinal mushroom that grows on the inner heartwood wall of Cinnamomum kanehirai Hay (Lauraceae), an endemic species that is used in Chinese medicine for its anti-tumor and immunomodulatory properties. In this study, we demonstrated that SY-1 profoundly decreased the proliferation of human colon cancer cells (COLO 205) through G0/G1 cell-cycle arrest (50–150 μM) and induction of apoptosis (>150 μM). Cell-cycle arrest induced by SY-1 was associated with a significant increase in levels of p53, p21/Cip1 and p27/Kip1, and a decrease in cyclins D1, D3 and A. In contrast, SY-1 treatment did not induce significant changes in G0/G1 phase cell-cycle regulatory proteins in normal human colonic epithelial cells (FHC). The cells were cultured in soft agar to evaluate anchorage-independent colony formation, and we found that the number of transformed colonies was significantly reduced in the SY-1-treated COLO 205 cells. These findings demonstrate for the first time that SY-1 inhibits human colon cancer cell proliferation through inhibition of cell growth and anchorage-independent colony formation in soft agar. However, the detailed mechanisms of these processes remain unclear and will require further investigation.

Nurses who learn to participate in suffering assessment are better able to understand spiritual needs of cancer patients. Cancer patients' views on the change mechanism in healing processes could provide essential information for nurses in developing an effective intervention programme. If nurses consider cultural factors that shape patients' experiences of spiritual suffering and the healing process, they could learn how to meet the needs of patients better from different cultural backgrounds.

Aim To investigate the association between specific dental therapy for periodontal disease and the risk of ischaemic stroke. Materials and Methods We conducted a population‐based cohort study that used data from the Taiwan National Health Insurance Research Database 2005 for the period of 2000–2013. Our observations focused on patients with the diagnoses of gingivitis or periodontitis with and without specific treatment and subsequent incidence of ischaemic stroke. Dental care services include dental scaling, intensive treatment (subgingival curettage and root planing) and tooth extraction. Multivariate Cox regression analysis was used to estimate the hazard ratios and corresponding 95% confidence intervals (95% CI). Results Compared with those in the gingivitis cohort, patients with periodontitis have a higher risk of ischaemic stroke and a lower survival rate of stroke over the 10‐year follow‐up period. After integrative dental care, both dental scaling and intensive treatment, the risk was reduced, especially in patients with periodontitis, while patients with periodontal disease may have an increased risk of stroke after tooth extraction therapy. Conclusions Our study showed that periodontitis is a risk factor for ischaemic stroke. Both dental scaling and intensive treatment for periodontal disease are associated with a lower risk of further ischaemic stroke events.

Survival prediction is highly valued in end-of-life care clinical practice, and patient performance status evaluation stands as a predominant component in survival prognostication. While current performance status evaluation tools are limited to their subjective nature, the advent of wearable technology enables continual recordings of patients' activity and has the potential to measure performance status objectively. We hypothesize that wristband actigraphy monitoring devices can predict in-hospital death of end-stage cancer patients during the time of their hospital admissions. The objective of this study was to train and validate a long short-term memory (LSTM) deep-learning prediction model based on activity data of wearable actigraphy devices. The study recruited 60 end-stage cancer patients in a hospice care unit, with 28 deaths and 32 discharged in stable condition at the end of their hospital stay. The standard Karnofsky Performance Status score had an overall prognostic accuracy of 0.83. The LSTM prediction model based on patients' continual actigraphy monitoring had an overall prognostic accuracy of 0.83. Furthermore, the model performance improved with longer input data length up to 48 h. In conclusion, our research suggests the potential feasibility of wristband actigraphy to predict end-of-life admission outcomes in palliative care for end-stage cancer patients.Clinical Trial Registration: The study protocol was registered on ClinicalTrials.gov (ID: NCT04883879).