68 research outputs found

    Turnover intention and coping strategies among older nursing assistants in China: a qualitative study

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    IntroductionWith the increasing aging population, older nursing assistants have made significant contributions to institutional eldercare. However, there is a high turnover rate among these workers, and it is crucial to address this issue and find ways to stabilize the workforce. This study aimed to explore the factors influencing turnover intention and coping strategies among older nursing assistants, in order to provide targeted assistance and guidance to reduce their intention to resign and ultimately lower the turnover rate.MethodsQualitative research methods were employed to conduct semi-structured interviews with older nursing assistants in Changsha. The data obtained from these interviews were then analyzed using a phenomenological analysis approach and NVIVO (QSR International, Doncaster, Australia) software version 11.0.ResultsIt is found that several factors influence turnover intention among older nursing assistants. Which include work pay, work environment, professional identity, external motivation, and work pressure. Additionally, the coping strategies employed by these individuals in relation to their intention to resign include self-regulation, seeking support, self-improvement, and exploring motivation.DiscussionIt is also evident from our study that reducing the turnover intention of older nursing assistants requires a collaborative effort from older adult care institutions, functional departments, and eldercare nursing assistants themselves. By addressing the factors influencing turnover intention and providing support and resources for coping strategies, we can work towards stabilizing the workforce and improving institutional eldercare

    Transcription control by the ENL YEATS domain in acute leukaemia

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    Recurrent chromosomal translocations producing a chimaeric MLL oncogene give rise to a highly aggressive acute leukaemia associated with poor clinical outcome. The preferential involvement of chromatin-associated factors as MLL fusion partners belies a dependency on transcription control. Despite recent progress made in targeting chromatin regulators in cancer, available therapies for this well-characterized disease remain inadequate, prompting the need to identify new targets for therapeutic intervention. Here, using unbiased CRISPR-Cas9 technology to perform a genome-scale loss-of-function screen in an MLL-AF4-positive acute leukaemia cell line, we identify ENL as an unrecognized gene that is specifically required for proliferation in vitro and in vivo. To explain the mechanistic role of ENL in leukaemia pathogenesis and dynamic transcription control, a chemical genetic strategy was developed to achieve targeted protein degradation. Acute loss of ENL suppressed the initiation and elongation of RNA polymerase II at active genes genome-wide, with pronounced effects at genes featuring a disproportionate ENL load. Notably, an intact YEATS chromatin-reader domain was essential for ENL-dependent leukaemic growth. Overall, these findings identify a dependency factor in acute leukaemia and suggest a mechanistic rationale for disrupting the YEATS domain in disease.K. LubinE. Wood

    Emergency tracheal intubation in 202 patients with COVID-19 in Wuhan, China:lessons learnt and international expert recommendations

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    Tracheal intubation in coronavirus disease 2019 (COVID-19) patients creates a risk to physiologically compromised patients and to attending healthcare providers. Clinical information on airway management and expert recommendations in these patients are urgently needed. By analysing a two-centre retrospective observational case series from Wuhan, China, a panel of international airway management experts discussed the results and formulated consensus recommendations for the management of tracheal intubation in COVID-19 patients. Of 202 COVID-19 patients undergoing emergency tracheal intubation, most were males (n=136; 67.3%) and aged 65 yr or more (n=128; 63.4%). Most patients (n=152; 75.2%) were hypoxaemic (Sao2 <90%) before intubation. Personal protective equipment was worn by all intubating healthcare workers. Rapid sequence induction (RSI) or modified RSI was used with an intubation success rate of 89.1% on the first attempt and 100% overall. Hypoxaemia (Sao2 <90%) was common during intubation (n=148; 73.3%). Hypotension (arterial pressure <90/60 mm Hg) occurred in 36 (17.8%) patients during and 45 (22.3%) after intubation with cardiac arrest in four (2.0%). Pneumothorax occurred in 12 (5.9%) patients and death within 24 h in 21 (10.4%). Up to 14 days post-procedure, there was no evidence of cross infection in the anaesthesiologists who intubated the COVID-19 patients. Based on clinical information and expert recommendation, we propose detailed planning, strategy, and methods for tracheal intubation in COVID-19 patients

    Cell transcriptomic atlas of the non-human primate Macaca fascicularis.

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    Studying tissue composition and function in non-human primates (NHPs) is crucial to understand the nature of our own species. Here we present a large-scale cell transcriptomic atlas that encompasses over 1 million cells from 45 tissues of the adult NHP Macaca fascicularis. This dataset provides a vast annotated resource to study a species phylogenetically close to humans. To demonstrate the utility of the atlas, we have reconstructed the cell-cell interaction networks that drive Wnt signalling across the body, mapped the distribution of receptors and co-receptors for viruses causing human infectious diseases, and intersected our data with human genetic disease orthologues to establish potential clinical associations. Our M. fascicularis cell atlas constitutes an essential reference for future studies in humans and NHPs.We thank W. Liu and L. Xu from the Huazhen Laboratory Animal Breeding Centre for helping in the collection of monkey tissues, D. Zhu and H. Li from the Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory) for technical help, G. Guo and H. Sun from Zhejiang University for providing HCL and MCA gene expression data matrices, G. Dong and C. Liu from BGI Research, and X. Zhang, P. Li and C. Qi from the Guangzhou Institutes of Biomedicine and Health for experimental advice or providing reagents. This work was supported by the Shenzhen Basic Research Project for Excellent Young Scholars (RCYX20200714114644191), Shenzhen Key Laboratory of Single-Cell Omics (ZDSYS20190902093613831), Shenzhen Bay Laboratory (SZBL2019062801012) and Guangdong Provincial Key Laboratory of Genome Read and Write (2017B030301011). In addition, L.L. was supported by the National Natural Science Foundation of China (31900466), Y. Hou was supported by the Natural Science Foundation of Guangdong Province (2018A030313379) and M.A.E. was supported by a Changbai Mountain Scholar award (419020201252), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA16030502), a Chinese Academy of Sciences–Japan Society for the Promotion of Science joint research project (GJHZ2093), the National Natural Science Foundation of China (92068106, U20A2015) and the Guangdong Basic and Applied Basic Research Foundation (2021B1515120075). M.L. was supported by the National Key Research and Development Program of China (2021YFC2600200).S

    3D Tensor Based Nonlocal Low Rank Approximation in Dynamic PET Reconstruction

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    Reconstructing images from multi-view projections is a crucial task both in the computer vision community and in the medical imaging community, and dynamic positron emission tomography (PET) is no exception. Unfortunately, image quality is inevitably degraded by the limitations of photon emissions and the trade-off between temporal and spatial resolution. In this paper, we develop a novel tensor based nonlocal low-rank framework for dynamic PET reconstruction. Spatial structures are effectively enhanced not only by nonlocal and sparse features, but momentarily by tensor-formed low-rank approximations in the temporal realm. Moreover, the total variation is well regularized as a complementation for denoising. These regularizations are efficiently combined into a Poisson PET model and jointly solved by distributed optimization. The experiments demonstrated in this paper validate the excellent performance of the proposed method in dynamic PET
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