Arterial spin labeling MR image denoising and reconstruction using unsupervised deep learning

Arterial spin labeling (ASL) imaging is a powerful magnetic resonance imaging technique that allows to quantitatively measure blood perfusion non-invasively, which has great potential for assessing tissue viability in various clinical settings. However, the clinical applications of ASL are currently limited by its low signal-to-noise ratio (SNR), limited spatial resolution, and long imaging time. In this work, we propose an unsupervised deep learning-based image denoising and reconstruction framework to improve the SNR and accelerate the imaging speed of high resolution ASL imaging. The unique feature of the proposed framework is that it does not require any prior training pairs but only the subject's own anatomical prior, such as T1-weighted images, as network input. The neural network was trained from scratch in the denoising or reconstruction process, with noisy images or sparely sampled k-space data as training labels. Performance of the proposed method was evaluated using in vivo experiment data obtained from 3 healthy subjects on a 3T MR scanner, using ASL images acquired with 44-min acquisition time as the ground truth. Both qualitative and quantitative analyses demonstrate the superior performance of the proposed txtc framework over the reference methods. In summary, our proposed unsupervised deep learning-based denoising and reconstruction framework can improve the image quality and accelerate the imaging speed of ASL imaging.     

Digital care technologies in people with dementia living in long-term care facilities to prevent falls and manage behavioural and psychological symptoms of dementia: a systematic review

European Journal of Ageing - Fall prevention and management of behavioural and psychological symptoms of dementia (BPSD) in long-term care (LTC) facility is a major challenge. The objective of this...     

社会力量参与公立互联网医院建设激励与约束机制研究

社会力量具备相应的经济基础和技术条件,对于公立互联网医院体系建设具有积极的促进作用。但是实践中仍然存在商业模式不完善、监管制度不健全等问题。基于经济学契约理论要义,提出在坚持激励与约束机制并举、平衡公私益关系的前提下,通过完善医保政策、构建互联网医疗服务价格分类管理机制来促进社会力量向医疗服务公益性目标回归,并通过构建完善的监督体制来约束部分社会力量的盲目逐利性行为。     

基于网络药理学和生物信息学研究苍附导痰丸治疗多囊卵巢综合征的分子机制＊

目的 探讨苍附导痰丸治疗多囊卵巢综合征（Polycystic ovary syndrome，PCOS）的潜在机制。方法 通过检索中药系统药理学数据库和分析平台（Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform，TCMSP）中苍附导痰丸组成药物的成分数据，筛选其有效成分和作用靶点；检索Drug Bank、GeneCards、OMIM、PharmGKB及Uniprot疾病数据库中PCOS相关靶点；检索GEO数据库，选择多囊卵巢综合征的差异表达基因。构建苍附导痰丸和PCOS成分、靶点间的相互关系网络，利用筛选出的关键靶点，构建蛋白互作（Protein-protein interaction，PPI）网络；在GO功能和KEGG信号通路富集的基础上，得出苍附导痰丸治疗PCOS的作用机制，进一步用分子对接技术验证靶点之间结合的可靠性。结果 共筛选出活性成分单体46个，159个苍附导痰丸治疗PCOS的共同靶点。结论 苍附导痰丸治疗PCOS具有多成分、多靶点、多通路的特点，推测苍附导痰丸可能通过调节炎症微环境从而改善肥胖型PCOS患者胰岛素抵抗，通过调节雌激素信号通路改善卵巢功能，因而可以改善肥胖及卵巢排卵的临床症状，为后期研究苍附导痰丸治疗PCOS的作用机制提供了新的理论支撑。     

Simultaneous Determination and Pharmacokinetics of Tetrandrine, Fangchinoline, and Cyclanoline in Rat Plasma by Ultra-High Performance Liquid Chromatography-Mass Spectrometry after Oral Administration of Stephaniae Tetrandrae Radix Extract

Objective: The objective of the study wasto develop a rapid and sensitive ultra?performance liquid chromatography?tandem massspectrometric method for the determination of tetrandrine, fangchinoline, and cyclanoline in rat plasma and to investigate their pharmacokinetics after oral administration of Stephaniae Tetrandrae Radix extracts. Methods: Sample pretreatment involved methanol pretreatment and liquid–liquid extraction of ethyl acetate from plasma with methanol. Tramadol was used as the internal standard. The analysis was performed using an high strength silica T3 column (100 mm × 2.1 mm, 1.8 μm) and a gradient elution method consisting of mobile phase solution A (0.1% formic acid in water) and B (acetonitrile) at a flow rate of 0.4 mL/min. The detection was performed using a triple quadrupole tandem mass spectrometer in the multiple reaction monitoring mode and using an electrospray ionization source in the positive ionization mode. Results: High efficiency was achieved with an analysis time of 4 min/sample. The calibration curve linear in the concentration range of 1250 ng/ml (R2 ≥ 0.9900) and the lower limit of quantification is 1 ng/ml. The intraday and interday precision (relative standard deviation) values were lower than 9.4. Accuracy (relative error) was within 10.3% at all three quality control levels. Conclusions: This method was successfully applied in pharmacokinetics of tetrandrine, fangchinoline, and cyclanoline in rats after oral administration of Stephaniae Tetrandrae Radix extracts. The maximum plasma concentration (Cmax) of tetrandrine, fangchinoline, and cyclanoline was 124.71 ± 16.08, 84.56 ± 3.28, and 57.61 ± 6.26 ng/ mL, respectively. The time to reach Cmax was 10.39 ± 3.04 for tetrandrine, 10.17 ± 3.04 for fangchinoline, and 6.40 ± 3.16 for cyclanoline. The pharmacokinetic results might help further guide the clinical application of Stephaniae Tetrandrae Radix.