Immunological mechanisms of fecal microbiota transplantation in recurrent Clostridioides difficile infection

Fecal microbiota transplantation (FMT) is a successful method for treating recurrent Clostridioides difficile (C. difficile) infection (rCDI) with around 90% efficacy. Due to the relative simplicity of this approach, it is being widely used and currently, thousands of patients have been treated with FMT worldwide. Nonetheless, the mechanisms underlying its effects are just beginning to be understood. Data indicate that FMT effectiveness is due to a combination of microbiological direct mechanisms against C. difficile, but also through indirect mechanisms including the production of microbiota-derived metabolites as secondary bile acids and short chain fatty acids. Moreover, the modulation of the strong inflammatory response triggered by C. difficile after FMT seems to rely on a pivotal role of regulatory T cells, which would be responsible for the reduction of several cells and soluble inflammatory mediators, ensuing normalization of the intestinal mucosal immune system. In this minireview, we analyze recent advances in these immunological aspects associated with the efficacy of FMT.     

Trends in management and outcomes of pulmonary embolism with a multidisciplinary response team

Journal of Thrombosis and Thrombolysis - Multidisciplinary pulmonary embolism (PE) response teams have garnered widespread adoption given the complexities of managing acute PE and provide a...     

Evidence-based strategies to reduce the incidence of postoperative delirium: a narrative review

Delirium is one of the most commonly occurring postoperative complications in older adults. It occurs due to the vulnerability of cerebral functioning to pathophysiological stressors. Identification of those at increased risk of developing delirium early in the surgical pathway provides an opportunity for modification of predisposing and precipitating risk factors and effective shared decision-making. No single delirium prediction tool is used widely in surgical settings. Multi-component interventions to prevent delirium involve structured risk factor modification supported by geriatrician input; these are clinically efficacious and cost effective. Barriers to the widespread implementation of such complex interventions exist, resulting in an ‘implementation gap’. There is a lack of evidence for pharmacological prophylaxis for the prevention of delirium. Current evidence suggests that avoidance of peri-operative benzodiazepines, careful titration of anaesthetic depth guided by processed electroencephalogram monitoring and treatment of pain are the most effective strategies to minimise the risk of delirium. Addressing postoperative delirium requires a collaborative, whole pathway approach, beginning with the early identification of those patients who are at risk. The research agenda should continue to examine the potential for pharmacological prophylaxis to prevent delirium while also addressing how successful models of delirium prevention can be translated from one setting to another, underpinned by implementation science methodology.     

Meralgia paraesthetica als Lagerungsschaden

Die Anaesthesiologie - Als Meralgia paraesthetica (MP) bezeichnet man eine zu den neurologischen Engpasssyndromen zählende Schädigung des aus dem Plexus lumbalis entspringenden sensiblen...     

糖尿病前期中医证型及证素特点分析＊

目的 探讨糖尿病前期的中医证型及证素分布特点。方法 检索中国知网、万方及维普三大数据库中收录的自建库以来有关糖尿病前期证型的临床研究文献，对中医证型进行规范整理，建立数据库，提取证素，运用数据挖掘技术中的关联分析、聚类分析探究证素分布规律。结果 共纳入10篇文献，总有效病例1620例，证型经规范处理后整理为18个，主要证型为脾虚痰湿证。共提取证素13个，主要病位证素为脾，主要病性证素为气虚、湿和痰，关联分析显示脾—湿支持度和置信度最高，聚类分析结果可得到3个聚类组。结论 糖尿病前期病位在脾，气虚、脾、痰、湿是常见证素，临床诊治糖尿病前期应注重从脾论治，需辨证施治。     

DEep learning-based rapid Spiral Image REconstruction (DESIRE) for high-resolution spiral first-pass myocardial perfusion imaging

The objective of the current study was to develop and evaluate a DEep learning-based rapid Spiral Image REconstruction (DESIRE) technique for high-resolution spiral first-pass myocardial perfusion imaging with whole-heart coverage, to provide fast and accurate image reconstruction for both single-slice (SS) and simultaneous multislice (SMS) acquisitions. Three-dimensional U-Net–based image enhancement architectures were evaluated for high-resolution spiral perfusion imaging at 3 T. The SS and SMS MB = 2 networks were trained on SS perfusion images from 156 slices from 20 subjects. Structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and normalized root mean square error (NRMSE) were assessed, and prospective images were blindly graded by two experienced cardiologists (5: excellent; 1: poor). Excellent performance was demonstrated for the proposed technique. For SS, SSIM, PSNR, and NRMSE were 0.977 [0.972, 0.982], 42.113 [40.174, 43.493] dB, and 0.102 [0.080, 0.125], respectively, for the best network. For SMS MB = 2 retrospective data, SSIM, PSNR, and NRMSE were 0.961 [0.950, 0.969], 40.834 [39.619, 42.004] dB, and 0.107 [0.086, 0.133], respectively, for the best network. The image quality scores were 4.5 [4.1, 4.8], 4.5 [4.3, 4.6], 3.5 [3.3, 4], and 3.5 [3.3, 3.8] for SS DESIRE, SS L1-SPIRiT, MB = 2 DESIRE, and MB = 2 SMS-slice-L1-SPIRiT, respectively, showing no statistically significant difference (p = 1 and p = 1 for SS and SMS, respectively) between L1-SPIRiT and the proposed DESIRE technique. The network inference time was ~100 ms per dynamic perfusion series with DESIRE, while the reconstruction time of L1-SPIRiT with GPU acceleration was ~ 30 min. It was concluded that DESIRE enabled fast and high-quality image reconstruction for both SS and SMS MB = 2 whole-heart high-resolution spiral perfusion imaging.     

Future perspectives: Novel Frontiers in Cancer Metastasis

Clinical & Experimental Metastasis -