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Abstract It remains a challenge to obtain biocompatible afterglow materials with long emission wavelengths, durable lifetimes, and good water solubility. Herein we develop a photooxidation strategy to construct near-infrared afterglow carbon nanodots with an extra-long lifetime of up to 5.9 h, comparable to that of the well-known rare-earth or organic long-persistent luminescent materials. Intriguingly, size-dependent afterglow lifetime evolution from 3.4 to 5.9 h has been observed from the carbon nanodots systems in aqueous solution. With structural/ultrafast dynamics analysis and density functional theory simulations, we reveal that the persistent luminescence in carbon nanodots is activated by a photooxidation-induced dioxetane intermediate, which can slowly release and convert energy into luminous emission via the steric hindrance effect of nanoparticles. With the persistent near-infrared luminescence, tissue penetration depth of 20 mm can be achieved. Thanks to the high signal-to-background ratio, biological safety and cancer-specific targeting ability of carbon nanodots, ultralong-afterglow guided surgery has been successfully performed on mice model to remove tumor tissues accurately, demonstrating potential clinical applications. These results may facilitate the development of long-lasting luminescent materials for precision tumor resection.

BackgroundPrevious studies have suggested that pregnant women with pulmonary hypertension (PH) have high maternal mortality. However, indexes or factors that can predict maternal death are lacking.MethodsWe retrospectively reviewed pregnant women with PH admitted for delivery from 2012 to 2020 and followed them for over 6 months. The patients were divided into two groups according to 10-day survival status after delivery. Predictive models and predictors for maternal death were identified using four machine learning algorithms: naïve Bayes, random forest, gradient boosting decision tree (GBDT), and support vector machine.ResultsA total of 299 patients were included. The most frequent PH classifications were Group 1 PH (73.9%) and Group 2 PH (23.7%). The mortality within 10 days after delivery was 9.4% and higher in Group 1 PH than in the other PH groups (11.7 vs. 2.6%, P = 0.016). We identified 17 predictors, each with a P-value < 0.05 by univariable analysis, that were associated with an increased risk of death, and the most notable were pulmonary artery systolic pressure (PASP), platelet count, red cell distribution width, N-terminal brain natriuretic peptide (NT-proBNP), and albumin (all P < 0.01). Four prediction models were established using the candidate variables, and the GBDT model showed the best performance (F1-score = 66.7%, area under the curve = 0.93). Feature importance showed that the three most important predictors were NT-proBNP, PASP, and albumin.ConclusionMortality remained high, particularly in Group 1 PH. Our study shows that NT-proBNP, PASP, and albumin are the most important predictors of maternal death in the GBDT model. These findings may help clinicians provide better advice regarding fertility for women with PH.

Fangcang shelter hospitals were established in China during the coronavirus disease 2019 (COVID-19) pandemic as a countermeasure to stop the spread of the disease. To our knowledge, no research has been conducted on mental health problems among patients in Fangcang shelter hospitals. This study aimed to determine the prevalence and major influencing factors of anxiety and depressive symptoms among COVID-19 patients admitted to Fangcang shelter hospitals. From February 23, 2020, to February 26, 2020, we obtained sociodemographic and clinical characteristics information of COVID-19 patients in Jianghan Fangcang Shelter Hospital (Wuhan, China) and assessed their mental health status and sleep quality. Data were obtained with an online questionnaire. The questionnaire consisted of a set of items on demographic characteristics, a set of items on clinical characteristics, the Self-Rating Anxiety Scale, Self-Rating Depression Scale, and Pittsburgh Sleep Quality Index. Three hundred seven COVID-19 patients who were admitted to Jianghan Fangcang Shelter Hospital participated in this study. The prevalence of anxiety and depressive symptoms were 18.6% and 13.4%, respectively. Poor sleep quality and having ≥ two current physical symptoms were independent risk factors for anxiety symptoms. Female sex, having a family member with confirmed COVID-19, and having ≥ two current physical symptoms were independent risk factors for depressive symptoms. Anxiety and depressive symptoms were found to be common among COVID-19 patients in Fangcang Shelter Hospital, with some patients being at high risk.