Environmental damage affects many aspects of healthcare, from extreme weather events to evolving population disease. Singapore's healthcare sector has the world's second highest healthcare emissions per capita, hampering the nation's pledge to reduce emissions by 2030 and achieve net zero emissions by 2050. In this review, we provide an overview of the impact environmental damage has on healthcare, including facilities, supply chain and human health, and examine measures to address healthcare's impact on the environment. Utilising the 'R's of sustainability - rethinking, reducing/refusing, reusing/repurposing/reprocessing, repairing, recycling and research - we have summarised the opportunities and challenges across medical disciplines. Awareness and advocacy to adopt strategies at institutional and individual levels is needed to revolutionise our environmental footprint and improve healthcare sustainability. By leveraging evidence from ongoing trials and integrating sustainable practices, our healthcare system can remain resilient against environment-driven challenges and evolving healthcare demands while minimising further impacts of environmental destruction.
Humans ; Climate Change ; Delivery of Health Care ; Singapore ; Conservation of Natural Resources ; Sustainable Development ; Environment

Inflammation plays a pivotal role in the etiology and progression of various diseases. In traditional Chinese medicine, the whole plants of Thesium chinense Turcz. and its preparations (e.g. Bairui Granules) have been employed to manage inflammatory conditions. While flavonoids were previously considered the primary anti-inflammatory components, other potentially active constituents have been largely overlooked and not thoroughly investigated. This study presents a novel finding that the total alkaloids of T. chinense (BC-Alk) are potent active substances underlying the traditional and clinical applications of T. chinense and Bairui Granules as anti-inflammatory agents. UPLC-MS/MS analysis identified the composition of BC-Alk as quinolizidine alkaloids. The anti-inflammatory efficacy of BC-Alk was evaluated using a lipopolysaccharide (LPS)-induced lung inflammation model in mice. Results demonstrated that BC-Alk significantly mitigated LPS-induced lung inflammation, attenuated the overproduction of IL-1β and the overproduction of inflammatory factors (TNF-α), and ameliorated lung tissue hyperplasia in mice in vivo. Mechanistic studies in vitro revealed that BC-Alk upregulated the expression of Nrf2 and its downstream proteins NQO1 and glutamate-cystine ligase and modifier subunit (GCLM), inhibited NF-κB phosphorylation, and suppressed NLRP3 activation. Collectively, these findings indicate that BC-Alk exerts potent inhibitory effects against lung inflammation by modulating Nrf2, NF-κB, and NLRP3 pathways. This study provides new insights into the anti-inflammatory constituents of T. chinense and Bairui Granules.
Animals ; Lipopolysaccharides/adverse effects* ; Alkaloids/pharmacology* ; NF-kappa B/metabolism* ; NF-E2-Related Factor 2/metabolism* ; NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Mice ; Signal Transduction/drug effects* ; Anti-Inflammatory Agents/pharmacology* ; Male ; Mice, Inbred C57BL ; Humans ; Drugs, Chinese Herbal/administration & dosage* ; Pneumonia/genetics*

OBJECTIVES: To explore the mediating role of sleep duration in the relationship between depression symptoms and myopia among middle school students. METHODS: This study was a cross-sectional research conducted using a stratified cluster random sampling method. A total of 1 728 middle school students were selected from two junior high schools and two senior high schools in certain urban areas and farms of the Xinjiang Production and Construction Corps. Questionnaire surveys and vision tests were conducted among the students. Spearman analysis was used to analyze the correlation between depression symptoms, sleep duration, and myopia. The Bootstrap method was employed to investigate the mediating effect of sleep duration between depression symptoms and myopia. RESULTS: The prevalence of myopia in the overall population was 74.02% (1 279/1 728), with an average sleep duration of (7.6±1.0) hours. The rate of insufficient sleep was 83.62% (1 445/1 728), and the proportion of students exhibiting depression symptoms was 25.29% (437/1 728). Correlation analysis showed significant negative correlations between visual acuity in both eyes and sleep duration with depressive emotions as measured by the Center for Epidemiologic Studies Depression Scale (with correlation coefficients of -0.064, -0.084, and -0.199 respectively; P<0.01), as well as with somatic symptoms and activities (with correlation coefficients of -0.104, -0.124, and -0.233 respectively; P<0.01) and interpersonal relationships (with correlation coefficients of -0.052, -0.059, and -0.071 respectively; P<0.05). The correlation coefficients for left and right eye visual acuity and sleep duration were 0.206 and 0.211 respectively (P<0.001). Sleep duration exhibited a mediating effect between depression symptoms and myopia (indirect effect=0.056, 95%CI: 0.029-0.088), with the mediating effect value for females (indirect effect=0.066, 95%CI: 0.024-0.119) being higher than that for males (indirect effect=0.042, 95%CI: 0.011-0.081). CONCLUSIONS Sleep duration serves as a partial mediator between depression symptoms and myopia in middle school students.
Humans ; Myopia/etiology* ; Male ; Female ; Depression/physiopathology* ; Cross-Sectional Studies ; Sleep ; Adolescent ; Students ; Child ; Time Factors ; Sleep Duration

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.