One-step hydrothermal synthesis of fluorescence carbon quantum dots with high product yield and quantum yield

A one-step hydrothermal synthesis of nitrogen and silicon co-doped fluorescence carbon quantum dots (N,Si-CQDs), from citric acid monohydrate and silane coupling agent KH-792 with a high product yield (PY) of 52.56% and high quantum yield (QY) of 97.32%, was developed. This greatly improves both the PY and QY of CQDs and provides a new approach for a large-scale production of high-quality CQDs. Furthermore, N,Si-CQDs were employed as phosphors without dispersants to fabricate white light-emitting diodes (WLEDs) with the color coordinates at (0.29, 0.32). It is suggested that N,Si-CQDs have great potential as promising fluorescent materials to be applied in WLEDs.Peer reviewe

An Efficient Synthesis and Photoelectric Properties of Green Carbon Quantum Dots with High Fluorescent Quantum Yield

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)To greatly improve the production quality and efficiency of carbon quantum dots (CQDs), and provide a new approach for the large-scale production of high-quality CQDs, green carbon quantum dots (g-CQDs) with high product yield (PY) and high fluorescent quantum yield (QY) were synthesized by an efficient one-step solvothermal method with 2,7-dihydroxynaphthalene as the carbon source and ethylenediamine as the nitrogen dopant in this study. The PY and QY of g-CQDs were optimised by adjusting reaction parameters such as an amount of added ethylenediamine, reaction temperature, and reaction duration. The results showed that the maximum PY and QY values of g-CQDs were achieved, which were 70.90% and 62.98%, respectively when the amount of added ethylenediamine, reaction temperature, and reaction duration were 4 mL, 180 °C, and 12 h, respectively. With the optimised QY value of g-CQDs, white light emitting diodes (white LEDs) were prepared by combining g-CQDs and blue chip. The colour rendering index of white LEDs reached 87, and the correlated colour temperature was 2520 K, which belongs to the warm white light area and is suitable for indoor lighting. These results indicate that g-CQDs have potential and wide application prospects in the field of white LEDs.Peer reviewedFinal Published versio

The association between complement C1q tumour necrosis factor-related protein-1 (CTRP-1) level and metabolic syndrome

Introduction: Complement C1q tumour necrosis factor-related protein (CTRP-1) is a member of the C1q protein superfamily that plays a role in metabolism. This retrospective study aimed to investigate associations between CTRP-1 and metabolic syndrome (MetS). Material and methods: This study screened subjects who had undergone regular health examinations at the Physical Examination Centre in the First People’s Hospital of Yinchuan (the Second Affiliated Hospital of Ningxia Medical University) between November 2017 and September 2020. The total recruited population included 430 subjects who had undergone regular health examinations, excluding 112 subjects with high glycated haemoglobin (HbA1c ≥ 7). Finally, the data of 318 participants were further analysed. Non-diabetic subjects were divided into 2 groups: one with MetS and one without MetS (controls). Serum CTRP-1 concentrations were evaluated using an enzyme-linked immunosorbent assay. Results: A total of 318 subjects were included, among whom 176 were diagnosed with MetS (MetS group) and 142 were not (non-MetS controls). The MetS group had significantly lower CTRP-1 levels than non-MetS controls (128.51 [111.56–143.05] vs. 138.82 [122.83–154.33] ng/mL, p < 0.001). Correlation analysis showed that serum CTRP-1 levels correlated negatively with body mass index (r = –0.161, p = 0.004), waist circumference (r = –0.191, p = 0.001), systolic blood pressure (r = –0.198, p < 0.001), diastolic blood pressure (r = –0.145, p = 0.010), fasting blood glucose (FBG) (r = –0.562, p < 0.001), fasting insulin (FIns) (r = –0.424, p < 0.001), and homeostasis model assessment of insulin resistance (HOMA-IR) (r = –0.541, p < 0.001). Multiple linear regression models showed that CTRP-1 levels were associated with MetS (p < 0.01). The lipid profile area under the curve (AUC) was comparable to those for FBG and FIns, and it was significantly higher than the AUCs for demographic variables. Conclusions: The results of this study suggest that the serum CTRP-1 level is negatively associated with MetS. CTRP-1 is a potential metabolism-related protein and is likely to be associated with lipid profiles in MetS

Decreased ventricular systolic function in chemotherapy-naive patients with acute myeloid leukemia: a three-dimensional speckle-tracking echocardiography study

BackgroundThe relationship between acute myeloid leukemia (AML) or acute lymphoblastic leukemia (ALL) and cardiac function is not well established. This study aimed to evaluate whether AML patients exist early myocardial damages prior to chemotherapy and to investigate its association with cardiovascular biomarkers.MethodsConventional echocardiography and three-dimensional speckle-tracking strain analysis were performed prospectively in 72 acute leukemia (AL) patients before any chemotherapy therapy (of whom 44 were AML patients, 28 ALL patients). The results were compared with those from 58 control group matched for age and gender.ResultsThere were no significant differences in conventional biventricular systolic function parameters between AL patients and controls. The left ventricular global longitudinal strain (LVGLS) and right ventricular free wall longitudinal strain (RVFWLS) were significantly lower in AL patients (−23.0 ± 1.4% vs. −24.1 ± 1.3% and −27.9 ± 7.1% vs. −33.0 ± 4.6%, respectively, P < 0.001 for all). Compared with ALL patients, AML patients had lower LVGLS and RVFWLS (−22.7 ± 1.3% vs. −23.5 ± 1.6% and −26.2 ± 7.6% vs. −30.4 ± 5.5%, respectively, P < 0.05 for all). LVGLS was lower in ALL patients compared with controls (−23.5 ± 1.6% vs. −24.7 ± 1.4%, P < 0.05), however, there was no difference in right ventricular systolic function parameters between the two groups. LVGLS in AL patients was independently correlated with left ventricular ejection fraction (LVEF) and the absolute number of circulating lymphocytes.ConclusionsOur findings suggest that baseline myocardial systolic function is lower in AL patients than controls. AML patients had lower baseline LVGLS and RVFWLS than controls and ALL patients. The decreased LVGLS is correlated with LVEF and the absolute number of circulating lymphocytes

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Dynamic Alu Methylation during Normal Development, Aging, and Tumorigenesis

DNA methylation primarily occurs on CpG dinucleotides and plays an important role in transcriptional regulations during tissue development and cell differentiation. Over 25% of CpG dinucleotides in the human genome reside within Alu elements, the most abundant human repeats. The methylation of Alu elements is an important mechanism to suppress Alu transcription and subsequent retrotransposition. Decades of studies revealed that Alu methylation is highly dynamic during early development and aging. Recently, many environmental factors were shown to have a great impact on Alu methylation. In addition, aberrant Alu methylation has been documented to be an early event in many tumors and Alu methylation levels have been associated with tumor aggressiveness. The assessment of the Alu methylation has become an important approach for early diagnosis and/or prognosis of cancer. This review focuses on the dynamic Alu methylation during development, aging, and tumor genesis. The cause and consequence of Alu methylation changes will be discussed