Twitter has become one of the most important social media platforms in science communication. During scientific conferences, Twitter can facilitate the communication between audience and speakers present at the venue and can extend the reach of a conference to participants following along from home. To examine whether Twitter activity can serve as a surrogate parameter for attendance at the RSNA conferences in 2019 and in 2020, and to characterize changes in topics discussed due to the virtual character of the 2020 RSNA conference.The Twitter API and R Studio were used to analyze the absolute number and frequency of tweets, retweets, and conference-related hashtags during the 2019 and 2020 RSNA conference. Topics of discussion were compared across years by visualizing networks of co-occurring hashtags.There was a 46% decrease in total tweets and a 39% decrease in individual Twitter users in 2020, mirroring a 43% decrease in registered attendees during the virtual conference. Hashtags related to social initiatives in radiology  were less frequently used in 2020 than in 2019.Twitter and congress attendance were highly related and interpersonal topics underwent less discussion during the virtual meeting. Overall engagement during the virtual conference in 2020 was lower compared to the in-person conference in 2019. Twitter activity and attendance on medical conferences are highly related.Twitter activity was lower during a virtual compared to an in-person conference.Interpersonal topics were less discussed during a virtual conference.Since its founding in 2006, Twitter has become one of the most important social media platforms in healthcare communication . RecentlTwitter has also become very popular at conferences for medical specialties, including radiology –14, for Up until 2020, Twitter activity during RSNA Annual Meetings has grown continuously. For example, an analysis of meeting-related hashtags at RSNA 2011 and RSNA 2012 showed an increase in Twitter usage of about 30% . HoweverInitially, we were interested in how Twitter might reflect the development of specific interests and topics  at RSNA conferences over the years. However, as RSNA was held virtually in 2020, we took the opportunity to analyze the impact of the virtual setting on engagement and topics under discussion.Tweets and their corresponding metadata were collected once a day during the 105th  and the 106th  RSNA Annual Meetings, as well as during the 3 days before and after each conference, by accessing the Twitter application programming interface (Twitter API) with the retweet library for R (version 4.0.5). Specifically, R Studio (Version 1.4.1106), a more user-friendly version of the statistic program R, was used to access the Twitter API and conduct the analysis. The Twitter API provides the opportunity to access Twitter data such as tweets, hashtags and user information . Relevant tweets were identified using the given congress hashtags (#rsna19 & #rsna2019 and #rsna20 & #rsna2020) and indexed with their unique Tweet ID. Importantly, all hashtags were set to lowercase before analysis. Simple retweets with no additional original text were excluded. Parameters collected included user information such as username, number of followers, and favorite counts; as well as the date and text of the tweet along with included hashtags.. “Non-mobile” refers to apps used on stationary devices  while “mobile” refers to apps used on smartphones and tablets . “Both” refers to apps that could be used on both types of devices. To examine differences in user profiles across years, the 50 most active users of each year were manually sorted into “business,” “personal,” and “education/non-profit” categories. Accounts were considered business users when they represented a company and not personal opinion . In contrast, accounts were considered “personal” if individual users tweeted a personal opinion . All accounts belonging to universities, institutions or non-profit organizations  were sorted in the category “educational/non-profit.” The proportion of tweets in each category was compared.Using R Studio, we performed descriptive analyses of meeting-related Twitter activity including number of tweets, retweets and favorites. We also examined metrics of individual Twitter users engaging with the conference, such as their number of followers and friends. “Followers” refers to people who subscribe to, or follow, an individual’s Twitter account who are then shown that person’s tweets in their feed; and “friends” refers to people that a Twitter user follows. We determined the number of friends and followers at the time of each tweet, as well as computed the median number of friends and followers for each user over 1 year. Also, changes in total number of friends and followers during the time course of the conferences were calculated. For qualitative analyses, we examined hashtags, username, and tweet source using R Studio. Hashtags were converted to lower case and then counted and sorted by frequency. To account for the unequal sample size, individual hashtags were set in relation to the total number of conference-related tweets in each respective year. Only hashtags that were used an average of 50 times or more in both years were included in the analysis. In addition, we examined the change in frequency of use for each hashtag and investigated the 75 most frequently co-occurring hashtag pairs across years. Furthermore, we examined which application was used to post each tweet and sorted them by primary application environment r was used for the Wilcoxon–Rank-test. P values < 0.05 were considered significant. Results are given as mean ± standard deviation unless otherwise noted. All statistical analyses were conducted using RStudio Version 1.4.1103.Using R Studio, differences in application environment were analyzed using chi-squared tests using Cramer’s V as the effect size. Robust ANOVA was used to examine categories. To compare counts of favorited tweets, retweets, friends, and followers across years, we used two-sample Wilcoxon Rank Sum tests after ruling out normal distribution using Shapiro–Wilk tests. The effect size M = 1.70 ± 3.61 vs. M = 1.44 ± 4.17; Z = − 9.23; p < 0.001; r = 0.05). Furthermore, Wilcoxon Rank Test revealed a difference in the mean number of favorites per tweet in 2019 compared to 2020 . Additionally, we found that in both years 94% of tweets had less than 30 retweets and favorites, indicating that only a small percentage of tweets had broad reach.Table Z = − 3.53; p < 0.001; r = 0.25). While they represented 2% (2019) and 5% (2020) of total users, respectively, their tweets reflected 34% (2019) and 48% (2020) of total tweets. We also calculated how many followers and friends the Top 50 gained during the meeting in both years. Interestingly, the Top 50 acquired more new followers in 2019 than in 2020 . In addition, the number of private, business and educational/non-profit users changed significantly across years : We observed more educational/non-profit users  and less private  and business  users among the Top 50 in 2020.We focused on the 50 most active Twitter users (Top 50) engaging in the conference each year in order to examine differences in user profiles across years. Not surprisingly, we observed a higher number of tweets per user among the Top 50 in 2019 than in 2020  ) than in 2020 (2147 tweets (32%)), while the percentage of tweets sent from non-mobile devices was lower in 2019  conferences.


Enho gene, which is associated with energy homeostasis. Preclinical studies using animal models have shown that adropin plays a role in enhancing glucose homeostasis and dyslipidemia. Lately, several studies on animal models have been performed to examine the therapeutic and pathophysiological effects of adropin in many disorders. The aim of this systematic review was to identify the ideal adropin dose in mice and rat animal models.Adropin is a hormone encoded by the in vitro studies, and factors affecting adropin levels were excluded from the study.We systematically searched PubMed, Science Direct, and Scopus databases from 2008 to 2020. The terms used in the search were “adropin,” “adropin doses in animal models,” “glucose homeostasis related to adropin,” and “adropin therapeutic effects on rats and mice.” Articles that included non-adropin doses, Of the total 179 qualified studies, six studies were included. We found that a daily injection of 450 nmol/kg of adropin for 3 days might be considered the optimum dose of effect in mice, whereas injection of 2.1 mg/kg once a day for 10 successive days might be the optimal effective dose in rats.Additional investigations are needed to determine the optimum dose of adropin to be used as a therapeutic intervention depending on the animal model. Enho gene, which is highly conserved in mammals and involved in energy homeostasis and lipid metabolism [The new peptide hormone adropin, which is composed of 76 amino acids highly expressed in the liver, brain, and plasma, is encoded by the tabolism . Adropintabolism . The nortabolism . Adropintabolism -7.Cpt1b, Cd36, and Pdk4 genes [In adropin knockout mice, a deficiency of adropin was found to be associated with hepatosteatosis and insulin resistance . On the k4 genes . These dSeveral studies ,8,10 havThis is a systematic review and it does not need ethical approval.in vitro studies, and factors affecting adropin level, as shown in We conducted a strong systematic search using the global web databases PubMed, Science Direct, and Scopus to determine the optimal dose of adropin in mice and rat animal models. To understand the mechanism of this myokine, we began by looking for adropin in general, followed by a hand search of abstracts of adropin and energy metabolism, especially in animal models (rats and mice). All selected abstracts were from the year 2008 until the present. In detail, we selected studies obtained through searching for the following keywords: “Adropin,” “adropin doses in animal models,” “glucose homeostasis related to adropin,” and “adropin therapeutic effects on rats and mice.” We identified 179 studies sorted by best match in PubMed and 119 studies in Science Direct and Springer sorted by most recent. We excluded articles that used non-adropin doses, in vivo, and well-defined studies describing all diseases that therapeutically required adropin were included in the study. We excluded in vitro and investigational studies explaining the factors affecting adropin levels. Furthermore, only dose-dependent adropin studies that provided relevant data about the therapeutic dose of adropin were included in the study. Studies providing data about specific therapeutic adropin doses and routes, The following data were extracted and presented in a table: Author(s), year, , mouse and rat type, adropin-producing company, and study aims. We collected data independently from six studies using a standardized criterion. All selected studies contained detailed information for the requested data.The literature review process performed in this study is summarized and presented in the flow chart in Overall, 6 of 179 studies were included in this systematic review. All included studies were published between 2008 and 2020, because adropin was discovered in 2008. The included studies were carried out on male and female rats and mice. Four studies were conducted using male C57BL/6 mice -12, and This systematic review aimed to determine the optimum dose of adropin by clarifying the doses used in animal models. The following paragraphs describe the doses of adropin used in different animal pathophysiological models.in vivo studies investigated the effect of adropin interventions in glucose homeostasis. The findings of these investigations showed that intraperitoneal administration of adropin reduced fasting blood glucose levels in mice [et al. [Several experimental  in mice ,12 and r in mice ,13. Trea in mice . In a st [et al. ,13. ThesIn addition to its role in glucose reduction in mice and rats, adropin intervention lowered the serum levels of total cholesterol, triglycerides, low-density lipoprotein cholesterol levels, and increased high-density lipoprotein cholesterol levels ,13, suggAdropin was reported to enhance glucose and insulin tolerance in DIO mice through insulin intracellular signaling through the Akt pathway in muscles. Adropin was suggested to induce sensitization of the insulin signaling pathways by increasing the expression of GLUT4 on the cell surface and inducing phosphorylation of Akt . The incIn the high-fat-diet mice model, five serial intraperitoneal injections of adropin (450 nmol/kg) were administered over 3 days. It was found that adropin adjusts the cardiac energy metabolism in obese mice . TreatmeAll studies included in our systematic review provide robust evidence on the efficiency of adropin intervention as a therapeutic agent for several pathophysiological conditions that affect glucose homeostasis and lipid metabolism in several types of animal models. Adropin intervention was reported to prevent hyperglycemia and hyperlipidemia; improve glucose tolerance; increase whole-body insulin sensitivity; inhibit hepatic glucose production; ameliorate hepatic insulin sensitivity; decrease cardiac glucose oxidation and cardiac pyruvate dehydrogenase activity; reduce serum levels of total cholesterol, triglycerides, low-density lipoprotein cholesterol, AST, ALT, alkaline phosphatase, and GGT; and increase the level of high-density lipoprotein cholesterol. In addition, adropin intervention downregulated peroxisome proliferator-activated receptor-gamma coactivator-1a, which regulates the expression of Cpt1b, Cd36, and Pdk4.In the studies using mice as an animal model, the optimal dose of adropin showing a therapeutic effect was 450 nmol/kg ,11,12. OIn the present review, we summarized all potential adropin intervention doses used in mice and rat models between 2008 and 2020. The optimal dose of adropin in mice, especially C57BL/6 mice, was 450 nmol/kg daily, whereas in rats, especially Wistar albino rats, it was 2.1 mg/kg/day. Additional investigations are needed to determine the optimal dose of adropin to be used as a therapeutic intervention depending on the animal model.FA and MBA: Collected and analyzed the data, formal analysis, funding acquisition, original draft preparation, reviewed and edited the manuscript. Both authors read and approved the final and revised copy of the manuscript.


Oxygen consumption is increased 6 months prior to tumour progression being visible on conventional MR imaging. However, presence of the Warburg effect, marking a switch from an infiltrative to a proliferative phenotype, could result in CMRO2 to appear unaltered in high-risk regions. Including information on biomarkers representing angiogenesis (rCBV and VSI) and hypercellularity (ADC) or protein concentration (APT) can omit misinterpretation due to the Warburg effect. Future research should evaluate these biomarkers in radiotherapy planning to explore the potential of advanced MR techniques to personalize target volume delineation with the aim to improve local tumour control and/or reduce radiation-induced toxicity.As microscopic tumour infiltration of glioblastomas is not visible on conventional magnetic resonance (MR) imaging, an isotropic expansion of 1–2 cm around the visible tumour is applied to define the clinical target volume for radiotherapy. An opportunity to visualize microscopic infiltration arises with advanced MR imaging. In this review, various advanced MR biomarkers are explored that could improve target volume delineation for radiotherapy of glioblastomas. Various physiological processes in glioblastomas can be visualized with different advanced MR techniques. Combining maps of oxygen metabolism (CMRO Patients diagnosed with glioblastoma face poor prognosis, as the median survival from initial diagnosis is less than 15 months . DelineaAn opportunity arises with advanced MR techniques, which offer the ability to visualize pathophysiological properties of tumours. These physiological processes might precede morphological changes on conventional MR imaging and thus provide information on microscopic tumour infiltration and/or high-risk regions for future relapse. With this information, the 10–20 mm isotropic expansion would be unnecessary as the CTV can be delineated, so that only the infiltration and high-risk regions are included. An improved CTV delineation could eventually lead to improved local tumour control and/or reduced radiation toxicity.In this review, the aim is to evaluate promising advanced MR techniques that have potential to improve CTV delineation for radiotherapy of glioblastoma in clinical practice. Key pathophysiological processes in glioblastoma development are discussed and, thereafter, promising advanced MR techniques are discussed that may visualize these physiological processes.Progression of glioblastoma is associated with hypoxic tumour microenvironment that is known to exist within glioblastomas. At cellular level, the glioblastoma stem-like cells (GSC), a specific subpopulation of cells that display principal stem cell properties like self-renewal and differentiation, thrive in harsh microenvironmental niches –11. Hypo3, as tumour expansion demands an increase in supply of oxygen and nutrients . T. T100]. Biopsy studies have shown that DWI is not helpful for the distinction between glioma infiltration and peritumoural brain tissue. The correlation between tumour cellularity and ADC value, which can be derived from DWI, in solid tumour tissue has been histologically proven by Kono et al. . The ADCp < 0.001) and a 9.2% decrease in signal intensity on FLAIR image (p < 0.001). Receiver-operating characteristic curves yielded AUC values of 0.566, 0.726, and 0.741 for ADC-only, FLAIR-only, and a combined model, respectively.Analysis of the recurrence site revealed that increased cell density can identify the site of recurrence at least 3 months before morphologic changes are visible on conventional MR imaging. Gupta et al. evaluated the correlation between low ADC values during treatment and recurrence location during follow-up . Only inA key characteristic of glioblastomas is its extensive, diffuse infiltration of tumour cells. This infiltrative behaviour is not fully visible on conventional MR imaging and is one of the reasons why proper management of gliomas is extremely difficult.DTI measures direction and magnitude of water diffusion based on data from a greater number (6 or more) of diffusion directions than DWI (3 directions). Water movement within white matter tracts is mainly restricted across the myelin sheaths, meaning that diffusion is more prevalent parallel to myelinated nerve fibers opposed to transverse . With inp = 0.27). Areas beyond tumour enhancement with a normal anisotropic component and an isotropic component greater than 10% compared to contralateral NAWM, however, could identify tumour infiltration with a sensitivity of 98% and specificity of 81%.In gliomas, regions with tumour infiltration can be identified with high sensitivity on DTI when information on the isotropic and anisotropic components of the diffusion tensor is split. To evaluate the potential of DTI to visualize tumour cell infiltration within peritumoural regions with increased T2-weighted signal intensity, Tropine et al. compared 20 patients with gliomas to 10 patients with meningiomas, in which no tumour infiltration is expected . CompariAlthough tumour infiltration can be visualized with high sensitivity, DTI does not seem useful for prediction of areas of future relapse. The integration of DTI for radiotherapy treatment planning of patients with high-grade gliomas was first explored by Jena et al. . DTI-basAn overview of the different biomarkers and corresponding advanced MR techniques is given in Table This literature review explored the potential of advanced MR imaging to visualize microscopic tumour infiltration and predict future areas of relapse in patients with glioblastoma. Studies using various techniques that (indirectly) visualize tumour growth/metabolism, vascularization, and hypoxia show that advanced MR biomarkers can precede morphologic changes on conventional MR imaging and could be the initial step towards personalization of radiotherapy planning.Although studies on multiple techniques have shown promising results, the integration of advanced MR imaging with radiotherapy planning in clinical practice remains limited. Careful consideration is taken regarding the introduction of these techniques into clinical practice, as it remains challenging how to incorporate the additional information resulting in either improved local tumour control or reduced radiation-induced toxicity.2 show a turning point at 90 and 60 days before recurrence, respectively. This switch could be an indication of the Warburg effect, in which aerobic glycolysis becomes dominant and cell proliferation is upregulated. This is in concordance with findings of DWI trials that evaluated progression-free survival; significant hypercellularity was reported at a median of 3.0 or 3.2 months prior to recurrence [2 or oxygen tension can result in overlooking potential sites of relapse. Depending on the time of acquisition, the oxygen consumption could appear normal after the Warburg effect has become dominant.Hypoxia and oxygen metabolism showed to be significantly altered approximately 6 months prior to tumour progression being visible on conventional MR imaging . Includicurrence , 104. AsA multiparametric approach, where multiple biomarkers were included, was shown to be superior to single-parameter predictive models , 115. In2 without altered perfusion can indicate vessel co-option or a temporary avascular state, which is predictive for future upregulation of angiogenesis and relapse. When a region shows increased rCBV or VSI with normal CMRO2, a switch from an infiltrative phenotype to a proliferative phenotype could have occurred [Combining perfusion and oxygen biomarkers allows for early indication of future sites of relapse while preventing misinterpretation due to the Warburg effect. A region with hypoxia or increased CMROoccurred . In thisIn a preclinical study, Baker et al. showed that, in some cases, vessel co-option can persist through to later stages, with the absence of the switch to angiogenesis for tumour vascularization . As vessIt is likely that a combination of advanced MR techniques will be required for optimal CTV delineation, but which parameters should or should not be included is an emerging and active field of research. The currently more established biomarkers, coming from widely available acquisitions and having software packages available for analysis, such as rCBV from DSC-MR imaging and ADC from DWI, are to be improved upon for CTV delineation via addition of more elaborate or novel biomarkers. Although DTI is a technique more widespread available already and infiltration along white matter tracts can provide valuable information, it might not be the most suitable technique for CTV delineation. For adaptation in clinical practice, additional research on the more novel MR techniques and their corresponding biomarkers is essential; however, these techniques could eventually be the missing piece of the puzzle. For example, CEST is becoming more and more available with the research community reaching consensus on acquisition and analysis  and qBOL2 or oxygen tension), angiogenesis (rCBV and VSI), hypercellularity (ADC), and protein concentration (APT) in radiotherapy planning of glioblastoma may result in more accurate CTV delineation, improved local tumour control, and/or reduced radiation-induced toxicity.The potential of advanced MR imaging for the visualization of microscopic tumour infiltration and prediction of future relapse sites has been presented. Including biomarkers that provide information on oxygen consumption (CMRO


Currently, there is no consensus regarding the inclusion of regions of central necrosis during volume of interest (VOI) delineation for radiomic analysis. The aim of this study was to assess how central necrosis affects radiomic analysis in PET. Methods: Forty-three patients, either with non-small cell lung carcinomas  or with pheochromocytomas or paragangliomas , were included retrospectively. VOIs were delineated with and without central necrosis. From all VOIs, 105 radiomic features were extracted. Differences in radiomic features between delineation methods were assessed using a paired t-test with Benjamini–Hochberg multiple testing correction. In the PPGL cohort, performances of the radiomic models to predict the noradrenergic biochemical profile were assessed by comparing the areas under the receiver operating characteristic curve (AUC) for both delineation methods. Results: At least 65% of the features showed significant differences between VOIvital-tumour and VOIgross-tumour . The AUCs of the radiomic models were not significantly different between delineation methods. Conclusion: In both tumour types, almost two-third of the features were affected, demonstrating that the impact of whether or not to include central necrosis in the VOI on the radiomic feature values is significant. Nevertheless, predictive performances of both delineation methods were comparable. We recommend that radiomic studies should report whether or not central necrosis was included during delineation.Background: Central necrosis can be detected on [ Tumour Radiomics aims to quantify the geometry and tracer uptake, including uptake heterogeneity, of tumours by using first order, shape and texture features and hypothesizing that these features can be used for tumour characterisation, prognostic stratification and response prediction in precision medicine . It is uThis study explores how central necrosis influences PET radiomic analysis by assessing the differences in radiomic features and the predictive performance of features extracted from VOIs delineated using an isocontour method with and without the manual addition of the region of central necrosis for two datasets of NSCLC and pheochromocytomas or paragangliomas (PPGL), catecholamine-producing neuroendocrine tumours that arise from the chromaffin cells of the adrenal medulla and extra-adrenal sympathetic paraganglia .18F]FDG PET/CT in a single academic centre were retrospectively included to study the effect of different aspects of central necrosis on the radiomic analysis. A cohort of patients with non-small cell lung-carcinomas , generally presenting a high tumour-to-background ratio, and a cohort of patients with pheochromocytomas or paragangliomas , generally presenting a low tumour-to-background ratio, were included.Subjects from two cohorts of patients who underwent an [18F]FDG PET/CT scan with the primary tumour located centrally in the field of view using the Biograph Duo or Biograph 40 mCT  at the Radboud University Medical Center between 2009 and 2014. Only tumours with a diameter larger than 30 mm were included to minimise the influence of partial volume effects and to be able to reliably quantify uptake heterogeneity [18F]FDG per kilogram of body weight started. The final time frame (50–60 min p.i.) of the dynamic series was used in the current study. Voxel sizes were 2.56 × 2.56 × 3.38 and 1.59 × 1.59 × 2.03 mm3 for the Biograph Duo PET/CT and Biograph 40 mCT PET/CT, respectively. This study has been reviewed and approved by the Commission on Medical Research Involving Human Subjects Region Arnhem-Nijmegen, the Netherlands. All patients signed an informed consent form.The NSCLC cohort is a previously published prospective cohort . Patientogeneity . Imaging18F]FDG PET/CT scan in the Radboud University Medical Center between 2011 and 2018 were retrospectively included. A selection of these patients has previously been described [18F]FDG  FDG uptake  was delineated using a semi-automatic threshold-based method and corrected for local background [peak) that was obtained using a sphere of 12 mm diameter [18F]FDG-avid tissues. VOIgross-tumour was generated by manually adding the volumes of central necrosis to VOIvital-tumour, using the low-dose CT as a visual reference. The necrotic tumour fraction (NTF) was determined using Equation (1):VOIs were delineated semi-automatically using 3DSlicer version 4.11  FDG PET significantly impacts radiomic feature values. Almost two-third of the features were affected, demonstrating that the influence of whether or not to include regions of central necrosis in the delineation of the tumour on the radiomic feature values is significant. However, no significant difference in the predictive performance of both delineation methods was observed. In order to advance reproducibility of radiomic research, radiomic studies should report on whether or not central necrosis was  included during delineation.Central necrosis of tumours on [


Central-line associated bloodstream infection (CLABSI) contributes to mortality and cost. While aseptic dressings and antibiotic-impregnated catheters can prevent extraluminal infections, intraluminal infections remain a source of CLABSIs with limited prevention options. Staphylococcus aureus, Staphylococcus epidermidis, Enterococcus faecium and Escherichia coli. In this proof-of-concept study, an electrochemical intravascular catheter (e-catheter) prototype capable of electrochemically generating hypochlorous acid intraluminally on the surface of platinum electrodes polarized at a constant potential of 1.5 VAg/AgCl was developed. After 24h of pre-polarization at 1.5 VAg/AgCl, their activity was tested by inoculating four clinical isolates derived from catheter-related infections, Figure 1. In vitro catheter and e-catheter models.E-catheters generated a mean HOCl concentration of 15.86±4.03 μM and had a mean pH of 6.14±0.79. e-catheters prevented infections with all four species, with an average reduction of 8.41±0.61 log10 CFU/mL at 48h compared to controls. Figure 3. Measurement of pH and HOCl at 48 hours in polarized e-catheters.Each dot represents a replicate; bars represent means.Figure 4. Prevention of infection after 48 hours of polarization (24 hours of infections) using e-catheters (polarized and non-polarized) compared to blank catheters.* indicates statistically significant reduction of cell counts in polarized e-catheter compared to blank catheter (p <0.05).Polarized e-catheters which generate low amounts of HOCl continuously should be further developed to prevent intraluminal infection.Haluk Beyenal, Ph.D, patent  Robin Patel, MD, 1928 Diagnostics (Consultant)BioFire Diagnostics (Grant/Research Support)ContraFect Corporation (Grant/Research Support)Curetis (Consultant)Hylomorph AG (Grant/Research Support)IDSA Infectious Diseases Board Review Course Mammoth Biosciences (Consultant)NBME Netflix (Consultant)Next Gen Diagnostics (Consultant)PathoQuest (Consultant)PhAST (Consultant)Qvella (Consultant)Samsung Selux Diagnostics (Consultant)Shionogi & Co., Ltd. (Grant/Research Support)Specific Technologies (Consultant)TenNor Therapeutics Limited (Grant/Research Support)Torus Biosystems (Consultant)Up-to-Date  Robin Patel, MD, BioFire  Involved: Self): Grant/Research Support; Contrafect  Involved: Self): Grant/Research Support; IDSA  Involved: Self): Editor's stipend; NBME, Up-to-Date and the Infectious Diseases Board Review Course  Involved: Self): Honoraria; Netflix  Involved: Self): Consultant; TenNor Therapeutics Limited  Involved: Self): Grant/Research Support; to Curetis, Specific Technologies, Next Gen Diagnostics, PathoQuest, Selux Diagnostics, 1928 Diagnostics, PhAST, Torus Biosystems, Mammoth Biosciences and Qvella  Involved: Self): Consultant


This article presents an investigation of heat transfer in a porous medium adjacent to a vertical plate. The porous medium is subjected to a magnetohydrodynamic effect and suction velocity. The governing equations are nondepersonalized and converted into ordinary differential equations. The resulting equations are solved with the help of the finite difference method. The impact of various parameters, such as the Prandtl number, Grashof number, permeability parameter, radiation parameter, Eckert number, viscous dissipation parameter, and magnetic parameter, on fluid flow characteristics inside the porous medium is discussed. Entropy generation in the medium is analyzed with respect to various parameters, including the Brinkman number and Reynolds number. It is noted that the velocity profile decreases in magnitude with respect to the Prandtl number, but increases with the radiation parameter. The Eckert number has a marginal effect on the velocity profile. An increased radiation effect leads to a reduced thermal gradient at the hot surface. Porous media are used in several applications involving a wide range of scientific and engineering fields. These diverse applications have motivated many researchers to explore the characteristics of porous media when subjected to various phenomena. Certain phenomena, such as heat transfer and fluid flow, have resulted in many scientific research articles explaining the meticulous details pertaining to heat transfer inside porous media. This number of articles is justified due to the varied applications where porous media play an important role. For example, foams that have several engineering applications are a form of porous media. Iasiello et al.  studied In recent years, interest in porous media has evolved to include recent trends such as entropy generation. This trend has gained momentum particularly due to the desire to design equipment that can perform by consuming less energy while also reducing waste. Many efforts have been made to understand entropy generation associated with various processes. For instance, Sayed and Abdel-Wahed  investigEntropy generation is an unwanted element that must be reduced to the greatest possible extent to enhance the performance of devices with respect to their energy consumption. Owing to its numerous applications, it is of paramount importance to understand the entropy characteristics of a porous medium with MHD adjacent to a hot vertical plate. This article is novel for its study of entropy generation in a porous medium adjacent to a vertical plate subjected to suction velocity, and magneto hydrodynamics have not been previously reported to the best of our knowledge. Thus, the current work is an attempt in that particular direction.x and y directions are considered along with the horizontal and vertical directions. The properties of the fluid are considered to be constant, apart from the density that allows the natural convection of fluid to take place. The temperature variation is considered only in the body-force term. The governing equations can be given as:The problem under investigation belongs to a steady flow of viscous, incompressible fluid across a porous medium bounded by a vertical plate, as shown in Continuity equation:Momentum equation:Energy equation:o is the constant suction velocity normal to the plate.The continuity (1) leads to:Using the Rosseland hypothesis ,37 as:In view of Equations (4)–(6), the Equations (2) and (3) can be shown to have the form as:The related boundary conditions of present problem are given as:The following non-dimensional parameters are usedSubstituting the above non-dimensional parameters into Equation (7) and (8) yields:The boundary conditions take the formThe entropy generated inside the porous medium due to various factors can be described as (16)Sg=kEquation (16) includes the entropy generation due to conductive and radiative heat transfer, viscous effects and the magnetic effectThe non-dimensional form of entropy can be deduced asThe first term in Equation (17) represents the entropy generation due to heat transfer; the second term highlights the fluid flow entropy; and the last term shows the entropy generated due to an applied magnetic field, which can be individually shown as−5. The results are compared to available data to ascertain the accuracy of the current methodology. The comparison is shown in The physical insight of the problem under investigation can be obtained by solving Equations (12), (13) and (17). These equations are solved numerically by the finite difference method. The outcome of the solution is the velocity and temperature profiles, along with the entropy generation. These equations are further simplified by converting them into first-order ordinary differential equations that make them easier to solve. The domain is divided into 1000 points in order to obtain the desired accuracy of 10The investigation was carried out with respect to various parameters involved in the governing equations, including the Prandtl number, radiation parameter, permeability parameter, Grashof number, viscous dissipation parameter, magnetic parameter, Eckert number, Reynolds number, and Brinkman number. The results are plotted in terms of velocity, the temperature profile in the porous domain, as well as entropy generation with respect to heat transfer, fluid flow, and magnetic effects.f), and viscous dissipation parameter (D) are shown in This section describes the temperature variations in the porous domain due to various parameters. Entropy is a term that describes the disorder or usefulness of energy in any process. Thus, the entropy presents an overview of how efficient a process is by reducing its irreversibility. The lesser the irreversibility, the better the system performance. Entropy can be generated due to various factors such as heat transfer, fluid flow, and magnetic effect. This section is devoted to understanding the different types of entropy generation associated with the current problem. The individual entropy is listed for three terms arising of Equation (17), which are thermal entropy (ST), fluid flow entropy (SF), and magnetic-field-related entropy (SM).The velocity profile is affected, to a greater extent, by the Prandtl number, Grashof number, radiation parameter, magnetic parameter, and permeability parameter, whereas the impact of the Eckert number, form-drag coefficient, and viscous dissipation parameter is significantly less.The velocity profile decreases owing to the Prandtl number and magnetic parameter. However, a reverse trend is observed with respect to the radiation parameter, permeability parameter, and Grashof number.The temperature profile decreases with increasing Prandtl number, whereas it increases with increase in the radiation parameter.The entropy generation increases with an increase in the Reynold’s number, Brinkman number, and radiation parameterThe fluid entropy dominates compared to thermal and magnetic entropy.The fluid and thermal entropy sharply decrease near the vertical plate, whereas magnetic entropy produces a different profile than the fluid and thermal entropy.The present article investigated heat transfer behavior in a fixed porous domain adjacent to the permeable vertical plate subjected to suction velocity and magnetic effects. The analysis was carried out with respect to entropy generation due to various parameters. This work revealed the following concluding points:


Enterobacterales isolates have increased and remain elevated in many US hospitals. Aminoglycoside (AMG) resistance often co-exist with resistance to other classes of antibiotics. A newer aminoglycoside, plazomicin, was evaluated against a large collection of MDR Enterobacterales clinical isolates from US hospitals.Multidrug-resistant (MDR) A total of 456 MDR isolates (1/patient) were collected from 32 US medical centers located in 23 states in 2018-2020 and susceptibility tested by broth microdilution method at a central laboratory. MDR was defined as nonsusceptible (NS) to ≥3 antimicrobial classes and extensively drug-resistant (XDR) as susceptible (S) to ≤2 classes. Isolates resistant to aminoglycosides and/or broad-spectrum cephalosporins were screened for aminoglycoside-modifying enzymes (AME), 16S rRNA methyltransferases, and β-lactamases by whole genome sequencing. 50/90, 0.5/1 mg/L) and showed MIC values 8- to 16-fold lower than amikacin . AMK S rates were 84.6% and 69.3% when EUCAST (≤8 mg/L) and USCAST (≤4 mg/L) breakpoints were applied, respectively. Among agents from other classes, S rates were 85.5% for meropenem, 88.4% for tigecycline, 49.3% for piperacillin-tazobactam, and 17.8% for cefepime; only the carbapenems and tigecycline were active against >50% of MDR isolates. PLZ retained activity against isolates NS to AMK (83.9%S), gentamicin , and/or tobramycin . PLZ showed markedly higher S rates than AMK against XDR (93.3% vs. 71.7%), AME producers (97.6% vs. 90.2%), and carbapenemase (CPE) producers (98.1% vs. 67.9%). PLZ was active against 99.0% of ESBL producers, while AMK S rates were 96.2%/87.0% as per the US FDA/EUCAST against these organisms. PLZ and AMK showed similar S rates when tested against GEN-NS isolates. GEN and TOB exhibited limited activity against MDR and all resistant subsets. PLZ inhibited 93.0% of the MDR isolates  (Research Grant or Support)Cidara Therapeutics, Inc. (Research Grant or Support)Cipla Therapeutics (Research Grant or Support)Cipla USA Inc. (Research Grant or Support)Melinta Therapeutics, LLC (Research Grant or Support)Pfizer, Inc. (Research Grant or Support) Jaideep Gogtay, n/a, Cipla Therapeutics (Employee)Cipla USA Inc. (Employee) Cheung Yee, MSc, PhD, Cipla Therapeutics (Employee) Sandhya Das, n/a, Cipla Therapeutics (Employee) Mariana Castanheira, PhD, AbbVie (formerly Allergan) (Research Grant or Support)Bravos Biosciences (Research Grant or Support)Cidara Therapeutics, Inc. (Research Grant or Support)Cipla Therapeutics (Research Grant or Support)Cipla USA Inc. (Research Grant or Support)GlaxoSmithKline (Research Grant or Support)Melinta Therapeutics, Inc. (Research Grant or Support)Melinta Therapeutics, LLC (Research Grant or Support)Pfizer, Inc. (Research Grant or Support)Qpex Biopharma (Research Grant or Support)Shionogi (Research Grant or Support)Spero Therapeutics (Research Grant or Support) Mariana Castanheira, PhD, Affinity Biosensors  Involved: Self): Research Grant or Support; Allergan  Involved: Self): Research Grant or Support; Amicrobe, Inc  Involved: Self): Research Grant or Support; Amplyx Pharma  Involved: Self): Research Grant or Support; Artugen Therapeutics USA, Inc.  Involved: Self): Research Grant or Support; Astellas  Involved: Self): Research Grant or Support; Basilea  Involved: Self): Research Grant or Support; Beth Israel Deaconess Medical Center  Involved: Self): Research Grant or Support; BIDMC  Involved: Self): Research Grant or Support; bioMerieux Inc.  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Pneumococcal vaccine recommendations in Canada include both age- and risk-based guidance. This study aimed to describe the burden of vaccine-preventable pneumococcal community acquired pneumonia (pCAP) and invasive pneumococcal disease (IPD) by age in hospitalized adults. Streptococcus pneumoniae was detected using blood and sputum culture, or urine antigen detection (UAD). Serotype was assigned using Quellung reaction, PCR, or serotype-specific UADs spanning the 24 serotypes in PCV13 and PPV23 vaccines. Data were categorized by age  and over time. Active surveillance for all-cause CAP and IPD in hospitalized adults was performed from 2010 to 2017, including laboratory results, patient demographics, and outcomes. S. pneumoniae was performed in 8912 of ACP cases, identifying 1264 (14.2%) as pCAP. Compared to non-pCAP, pCAP cases were more likely to be admitted to intensive care units and require mechanical ventilation. These serious outcomes, as well as mortality, were more prominent in bacteremic pCAP and IPD. Risk factors for death in pCAP included aged 75+ years, immune compromising conditions, and BMI < 18.5. When categorized by age, the proportion of individuals aged 65+ years for pCAP and IPD was 49.8% and 48.6%, and the 50-64 year age cohort represented 31.3% and 29.9%, respectively. The contributions of PCV13 and PPV23 serotypes remained relatively stable over time, and overall represented 57.6% and 90.9% for pCAP, and 35.0% and 72.0% for IPD, respectively. 11129 ACP cases and 216 cases of IPD (non-CAP) were identified. A laboratory test for Seven years following infant PCV13 immunization programs in Canada, PCV13 and PPV23 serotypes in pCAP and IPD remained predominant causes of pneumococcal disease. Serious outcomes were particularly evident in adults 50+, suggesting pneumococcal vaccines should be encouraged in this age group.Jason J. LeBlanc, PhD, FCCM, D[ABMM], GSK (Research Grant or Support)Merck (Grant/Research Support)Pfizer (Grant/Research Support) Todd F Hatchette, MD, GSK (Grant/Research Support)Pfizer (Grant/Research Support) Melissa K. Andrew, MD, PhD, GSK (Grant/Research Support)Pfizer Sanofi Seqirus (Advisor or Review Panel member) Allison McGeer, MSc,MD,FRCPC,FSHEA, GlaxoSmithKline (Advisor or Review Panel member)Merck Pfizer  Louis Valiquette, MD, M.Sc., Cubist (Consultant)GSK (Grant/Research Support)Merck (Consultant)Optimer (Consultant)Pfizer (Grant/Research Support) Shelly McNeil, FRCPC, MD, GSK (Grant/Research Support)Pfizer (Grant/Research Support)Sinofi Pasteur (Grant/Research Support)


The combination of LVEDA and E/E′ showed incremental predictive ability for fluid responsiveness compared with LVEDA  or pulse pressure variation , yielding the highest AUROC of 0.78 . The combined index of echocardiographic variables reflecting LV dimension (LVEDA) and diastolic compliance and filling (E/E′) is a potentially useful predictor of fluid responsiveness.We investigated the role of echocardiographic indices consisting of left ventricular end-diastolic area (LVEDA) in combination with Doppler-derived surrogates of diastolic compliance and filling , tissue Doppler-derived early (E′) diastolic, late (A′) diastolic, or peak systolic (S′) velocity of the mitral annulus) in predicting fluid responsiveness in off-pump coronary surgery. Hemodynamic and echocardiographic variables were prospectively assessed under general anesthesia before and after a fluid challenge of 6 mL/kg during apnea at atmospheric pressure in 64 patients with LV ejection fraction ≥40%. Forty patients (63%) were fluid responders (≥15% increase in stroke volume index). E/E′ and E′/S′ could predict fluid responsiveness with area under the receiver operating characteristic curve (AUROC) of 0.71 (95% confidence interval [CI], 0.56–0.85;  For perioperative and critical care, appropriate fluid resuscitation guided by reliable preload indices is of pivotal importance as only half of the patients are fluid responsive  and supeBy contrast, the assessment of static preload indices is feasible regardless of heart rhythm or heart–lung interaction, while they are unable to predict fluid responsiveness. Indeed, the use of invasively acquired measures of filling pressures using a pulmonary artery catheter (PAC) for assessing fluid responsiveness has been discouraged . SimilarHypothetically, combining LVEDA and these indices would provide more insights regarding the LV dimension, as well as diastology (compliance and filling) that governs the ventricular response to a fluid challenge , which cThe current study was conducted at Severance Cardiovascular Hospital, Yonsei University Health System, Seoul, Republic of Korea, after being approved by the institutional review board (IRB number: 4-2017-0403) and registered at the clinicaltrials.gov (NCT03222778) before recruitment started. This study was conducted following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines and according to the Declaration of Helsinki. A total of 66 patients scheduled for off-pump coronary surgery between August 2017 and March 2020 were enrolled after obtaining written informed consent. The exclusion criteria were kidney disease requiring renal replacement therapy, heart rhythm other than sinus, LV ejection fraction <40%, lateral wall motion abnormalities, or any valvular heart disease of ≥moderate severity.2O. The inspired oxygen fraction was 0.4 with air. A PAC and transesophageal echocardiography (TEE) probe were inserted in all patients and the former was connected to a Vigilance II monitor  assessing continuous cardiac output. PPV was acquired from the radial arterial pressure waveform connected to Philips Intellivue MP70 . The target mean arterial pressure during surgery was 60–80 mmHg, which was maintained by administering norepinephrine, vasopressin (added when the norepinephrine requirement exceeded 0.3 μg/kg/min), or nicardipine as necessary.All subjects received standardized anesthetic care as previously described . In brie®; Fresenius Kabi, Bad Homburg, Germany).Assessment of hemodynamic and echocardiographic variables was performed 15 min after the insertion of a PAC under general anesthesia (baseline) and 10 min after the completion of fluid challenge. A fluid challenge of 6 mL/kg  was performed for 10 min using 6% balanced hydroxyethyl starch 130/0.4 , pulmonary artery occlusion pressure (PAOP), cardiac index and stroke volume index (SVI). PPV was obtained as an average of 4 cycles of 8 s. Filling pressures were measured during apnea at atmospheric pressure. For cardiac index and SVI, the average of 3 serial STAT mode measurements was recorded.Echocardiographic variables included LVEDA, E, E′, A′ and S′. They were all measured with TEE during apnea at atmospheric pressure by a single examiner (J-K Shim). LVEDA measurements were obtained from the transgastric mid-papillary short axis view and E, E′, A′ and S′ measurements were obtained from the midesophageal 4-chamber view. An average of 3–5 beats was recorded for LVEDA ), E, E′, A′ and S′. Pulsed-wave Doppler measurement of E velocity was performed between the mitral leaflet tips. Tissue Doppler imaging (TDI) measurements of the E′, A′ and S′ were carried out at the lateral mitral annulus . LVEDA and E, E′, A′ and S′ values were all measured thrice each and the average value was used for analysis. Surgical incision was deferred until the completion of the last measurement. Measurements of the echocardiographic variables were conducted by J-K Shim who was blinded to the data on hemodynamic variables. Vasopressor requirement and plateau inspiratory pressure at the time of measurement were also recorded.The primary endpoint was to assess the predictive abilities of the combined echocardiographic preload indices consisting of LVEDA and Doppler-derived parameters of diastolic compliance and filling  for fluid responsiveness (defined as a ≥ 15% increase in SVI). The secondary endpoint was to assess the predictive abilities of PPV, CVP, PAOP and LVEDA on fluid responsiveness and compare the predictive abilities of the combined echocardiographic preload indices with those of LVEDA or PPV alone.Statistical analyses were conducted using SAS  and SPSS for Windows . Sample size was predicted under the assumption that the area under the receiver operating characteristic curve (AUROC) of the combined echocardiographic index would be greater by 0.2 than the previously reported AUROC of 0.64 of LVEDA alone , to aim Intra-observer variabilities of the measured echocardiographic variables were assessed using the intra-class correlation coefficient by a one-way random effects model. An intra-class coefficient of more than 0.85 usually indicates that the measurement is consistent.t-test or Mann–Whitney U test according to the results of the normality test. Intergroup comparisons of categorical variables between fluid responders and non-responders were conducted using the chi-square test or Fisher’s exact test. Intragroup comparisons of continuous variables at baseline and after fluid challenge in both responders and non-responders were carried out using the paired t-test or the Wilcoxon signed-rank test according to the results of the normality test.Continuous variables were first assessed for their normality using the Kolmogorov–Smirnov test. Intergroup comparisons of continuous variables between fluid responders and non-responders were performed using the independent The AUROC was calculated for the potential candidates of preload indices to test their predictive ability for fluid responsiveness. To investigate the incremental value of combining echocardiographic indices for predicting fluid responsiveness, we performed multivariable logistic regression analysis and the AUROCs of the tested variables were compared using the DeLong test. A nomogram was constructed using a combination of echocardiographic indices showing the highest AUROC in the multivariable analysis.n (%). A value of p < 0.05 was considered statistically significant.Data are presented as mean ± standard deviation (SD), median (25–75% interquartile range (IQR)), or The PAC could not be properly positioned in two patients who were then excluded from the data analysis; thus, data from only 64 patients were analyzed. A total of 40 patients (63%) were fluid responders. The intra-class coefficients of echocardiographic variables that were measured thrice and averaged were 0.96, 0.98, 0.96, 0.94 and 0.96 for LVEDA, E, E′, S′ and A′, respectively, indicating excellent reproducibility. Intergroup comparisons of patients’ characteristics between responders and non-responders are displayed in Intergroup comparisons of hemodynamic variables and invasive indices of preload between responders and non-responders are displayed in Intergroup comparisons of echocardiographic indices of preload between responders and non-responders are displayed in p = 0.002). Among the echocardiographic indices of preload, E/E′ and E′/S′ could predict fluid responsiveness with AUROCs of 0.71  and 0.68 , respectively. The combination of LVEDA and E/E′ in the multivariable model showed incremental predictive ability for fluid responsiveness compared with LVEDA or PPV alone (p < 0.001). Power calculation from the observed results yielded a power of 87%. The AUROC of the combination of LVEDA and E/E’ was significantly larger than that of the LVEDA alone (p = 0.020) while the AUROC of the PPV was not when compared to that of the LVEDA (p = 0.326).The results of ROC curve analysis of the potential candidates of preload indices are displayed in PV alone , yieldinp value of the Hosmer–Lemeshow goodness-of-fit test was 0.384, indicating the adequacy of the constructed nomogram. The mean absolute error of the calibration plot of the nomogram was 0.021. This result indicates good correlation between the predicted probability proposed by the nomogram and the actual probability of fluid responsiveness , which are considered as poor for clinical use, while E’/A’ or LVEDA could not. Among the invasive preload indices, only PPV was able to predict fluid responsiveness, but at a lower predictive power (AUROC of 0.70) as well, whereas CVP and PAOP could not. Of the combinations, LVEDA and E/E′ yielded the highest predictive power (AUROC of 0.78), whereas the combinations of LVEDA and E′/S′ or E′/A′ could poorly predict fluid responsiveness , which may be attributable to the following. Global diastolic filling is mainly related to both early relaxation (active) and late elastic properties (passive) . AlthougPPV is one of the most useful dynamic preload indices assuming that all of the conditions for proper heart–lung interaction are met . HoweverIn theory, this combined static index of LVEDA and E/E’ can potentially be applied to guide fluid therapy in clinical situations not suitable for the evaluation of dynamic indices or passive leg raising. However, being a pilot study, we measured these parameters in patients with sinus rhythm under closed chest condition, which merits further studies in a wide variety of patients in different clinical scenarios to prove its predictive ability on fluid responsiveness independent from heart-lung interaction or heart rhythm.This study is subject to the following limitations. First, we used the lateral mitral annulus for TDI assessment. For simplicity, lateral E′ velocity is recommended given the potential influence of the right ventricle on septal E′ velocity . HoweverIn conclusions, the combined index of echocardiographic variables reflecting LV dimension (LVEDA) and diastolic compliance and filling (E/E′) can be a useful predictor of fluid responsiveness in anesthetized patients with preserved LV ejection fraction undergoing surgical coronary revascularization, showing better predictive ability than PPV in this subset of patients.


Background: Dynamic preload parameters such as pulse pressure variation (PPV) and stroke volume variation (SVV) have widely been used as accurate predictors for fluid responsiveness in patients under mechanical ventilation. To circumvent the limitation of decreased cyclic change of intrathoracic pressure, we performed an intermittent PEEP challenge test to evaluate whether PPV or SVV can predict fluid responsiveness during one-lung ventilation (OLV).Methods: Forty patients undergoing OLV were analyzed. Baseline hemodynamic variables including PPV and SVV and respiratory variables were recorded after chest opening in lateral position under OLV (T1). Five minutes after application of PEEP 10 cmH2O, the parameters were recorded (T2). Thereafter, PEEP was withdrawn to 0 cmH2O for 5 minutes (T3), and fluid loading was performed with balanced crystalloid solution 6 mL/kg of ideal body weight for 5 minutes. Five minutes after completion of fluid loading, all variables were recorded (T4). The patient was classified as fluid responder if SV increased ≥10% after fluid loading and as non-responder if SV increased <10%.Results: Prediction of fluid responsiveness was evaluated with area under the receiver operating characteristic (ROC) curve (AUC). Change in stroke volume variation (ΔSVV) showed AUC of 0.9 (P < 0.001), 95% CI = 0.82-0.99, sensitivity = 88%, specificity = 82% for discrimination of fluid responsiveness. Change in pulse pressure variation (ΔPPV) showed AUC of 0.88 (P < 0.001), 95% CI = 0.78-0.97, sensitivity = 83%, specificity = 72% in predictability of fluid responsiveness. Cardiac index and stroke volume were well maintained after PEEP challenge in non-responders while they increased in responders.Conclusions: ΔPPV and ΔSVV induced by PEEP challenge are reliable parameters to predict fluid responsiveness as well as very good predictors of fluid unresponsiveness during OLV. Optimal fluid management during lung surgery is of significant importance and remains challenging for anesthesiologists. Generally, restrictive fluid management is recommended for lung surgery to prevent acute lung injury or impairment of respiratory gas exchange from fluid overload During lung surgery, fluid management using dynamic parameters is complex because of physiologic alteration by opened non-dependent thorax, one-lung ventilation (OLV) and protective ventilation technique with low tidal volume. These conditions affect the ability of PPV and SVV to predict fluid responsiveness 2O may improve predictability of dynamic parameters on fluid responsiveness during OLV.To our knowledge, challenge test to improve the diagnostic ability of dynamic parameters have not been studied during OLV. We hypothesized that temporary increase in PEEP from 0 to 10 cmHAfter approval from the Institutional Review Board of Hallym University Kangnam Sacred Heart Hospital  and registration at ClinicalTrials.gov (NCT 03794414), we conducted the prospective observational study in 40 patients undergoing lung surgery under OLV .Exclusion criteria are as follows: known preoperative cardiac disease including arrhythmia, moderate to severe valvular heart disease, moderate to severe pericardial effusion, left ventricular ejection fraction <40%, moderate to severe chronic obstructive lung disease with 1-second forced expiratory volume <60% of predicted values, contraindication to esophageal Doppler monitoring probe insertion  and severe obesity , and an entropy value was maintained between 40 and 60. All patients received 0.6 mg/kg of rocuronium for muscle relaxation. When maximal suppression was reached on train-of-four stimulation, left-sided or right-sided double-lumen tube  was inserted for OLV. Correct position and depth was confirmed with fiberoptic bronchoscope. Radial artery was cannulated for continuous arterial blood pressure monitoring. Forced air warmer was applied and core temperature was maintained above 36.0 °C. Following induction of anesthesia, an esophageal Doppler probe  was inserted into the esophagus by a well-trained anesthesiologist. The esophageal Doppler probe was placed in the optimal position by monitoring aortic visual and auditory signals displaced on the CardioQ-ODM+ monitor .Following position change to lateral position, OLV was initiated with tidal volume of 6 mL/kg of ideal body weight, an inspired oxygen fraction of 0.5 and I:E ratio of 1:1.5 without PEEP using volume-controlled mode. Respiratory rate was adjusted to maintain end-tidal carbon dioxide partial pressure between 35 and 40 mmHg. An inspired oxygen fraction was elevated by 0.1 if oxygen saturation fell below 92%.Heart rate, mean arterial blood pressure and PPV were recorded through the patient monitor . Dynamic compliance, mean airway pressure and peak inspiratory pressure were obtained from the anesthesia ventilator machine . Cardiac index, stroke volume and SVV were acquired from CardioQ-ODM+ monitor. PPV and SVV were calculated as follows:The parameters were displayed on the CardioQ-ODM+ monitor every 10 seconds. The parameters were recorded on three consecutive respiratory cycles and averaged for statistical analysis. Each measurements were performed under stable hemodynamic state with no inotropes or vasopressors. The changes in PPV and SVV after PEEP challenge were calculated as follows:2O of PEEP was applied. Five minutes after application of PEEP 10 cmH2O, the parameters were recorded (T2). Thereafter, PEEP was withdrawn to 0 cmH2O for 5 minutes and the parameters were recorded (T3). Fluid loading was performed with balanced crystalloid solution  6 mL/kg of ideal body weight for 5 minutes. Five minutes after completion of fluid loading, all parameters were recorded (T4). All measurements were made in a hemodynamically stable state with minimum or no surgical manipulation.The hemodynamic and respiratory parameters were recorded at 4 predetermined time points Fig. . BaselinTo determine fluid responders, stroke volume displayed on the CardioQ-ODM+ monitor was analyzed. The patient was classified as fluid responder if stroke volume increased ≥10% after fluid loading and as non-responder if stroke volume increased <10% ® Version 10.0.1.0. and SPSS 22 for Windows . All data are expressed as mean ± SD, median (interquartile range) or number (percentage). Comparisons of demographic data between responders and non-responders were assessed with Student's t-test for continuous variables and Chi-square test for categorical variables. For nonparametric data analysis, Mann-Whitney U test or Fisher's exact test were used. Comparisons of hemodynamic variables before and after PEEP challenge or fluid loading were assessed with paired t-test. For nonparametric data analysis, Wilcoxon signed rank test was used.Statistical analysis was performed using MedcalcROC curves were generated for PPV1, PPV2, △PPV, SVV1, SVV2 and △SVV. To determine the diagnostic ability of the variables to predict fluid responsiveness, the area under the curve  were calculated and compared using Hanley-McNeil test A gray zone was used to determine the values which provide inconclusive information using Youden's index. The values in the range of gray zone mean formal conclusion cannot be obtained. Inconclusive region was defined as values with a sensitivity lower than 90% or specificity lower than 90% The sample size was calculated using PASS . The sample size was determined on the basis of ROC analysis. We considered augmented PPV by PEEP challenge to predict fluid responsiveness if the area under the ROC curve was >0.8. Assuming that the null hypothesis was 0.5 (no discrimination) with type 1 error = 0.05 and type 2 error = 0.1, a minimum of 36 patients were needed. Considering a dropout rate of 10%, 40 patients were enrolled.In our study, 44 patients were assessed for recruitment. Four patients met our exclusion criteria , and 40 patients were analyzed Fig. . 18 patiHemodynamic and respiratory variables at baseline (T1) and after PEEP challenge T2) are described in Table  are descHemodynamic and respiratory variables before T3) and after fluid loading (T4) are described in Table  and afte1, PPV2, ΔPPV, SVV1, SVV2 and ΔSVV were used to determine responders and non-responders with ROC analysis. ΔSVV showed successful discrimination of fluid responsiveness  predictive value = 80, 95% CI = 62-97, (-) predictive value = 90, 95% CI = 76-100). ΔPPV showed AUC of 0.88  predictive value = 71, 95% CI = 52-90, (-) predictive value = 84, 95% CI = 67-100) and SVV2 showed AUC of 0.85  in predicting fluid responsiveness. Also, ΔSVV and ΔPPV were very good predictors of fluid unresponsiveness during OLV. AUC of PPV2 in predicting fluid responsiveness was 0.79 (P < 0.001). However, PPV1 and SVV1 did not predict fluid responsiveness.Prediction of fluid responsiveness was evaluated using ROC analysis Table  and 4. T1, PPV2, ΔPPV, SVV1, SVV2, ΔSVV) to predict fluid responsiveness was depicted using gray zone analysis  and only 8 patients were included. The gray zone of SVV1 was between 2.3 and 7.9 with 31 numbers of patients. By PEEP application, the gray zone of SVV2 also decreased from 4.3 to 6.8 with 12 numbers of patients. ΔSVV showed gray zone from -0.1 to 1.3 and 16 patients were included.The inconclusive region of dynamic parameters  application to the dependent lung is known to help reduce blood flow to the nondependent lung. High level of PEEP (15-20 cmH2O) is known to decrease cardiac output, although the precise mechanism to PEEP during OLV is not simple and the intrathoracic response appear multiple and complex The present study has the clinical implication that the simple PEEP application for short period of time improved the predictive power of PPV and SVV of fluid responsiveness in patients within the gray zone. Also, there was no decrease in cardiac index and stroke volume with optimal level of PEEP application. Rather, cardiac index and stroke volume increased only in fluid responders after PEEP application. It is not clear but we assume it is associated with hypoxic pulmonary vasoconstriction since PEEP (5 to 10 cmHThere are several limitations with the present study. First, the total number of patients may not be sufficient to generalize our result to all patients. Further studies with larger number of patients calculated with precise parameter are needed to describe the physiologic mechanism of PEEP on dynamic parameters during OLV. Second, we used esophageal Doppler for measurement of dynamic parameters. Esophageal Doppler probe frequently needed repositioning during the operation. However, we measured cardiac output when optimal signal from descending aorta was obtained with minimum surgical manipulation. Several studies have evaluated the use of esophageal Doppler during OLV and validated its use of measuring cardiac output compared to standard method of thermodilution In conclusion, the present study demonstrates that PEEP challenge maneuver increased the diagnostic ability of PPV and SVV of predicting fluid responsiveness and fluid unresponsiveness during OLV. The use of ΔPPV and ΔSVV after PEEP challenge would be helpful to guide fluid management in patients under OLV.


Sci., 2019, 10, 2653–2662, DOI: 10.1039/C8SC03426E.Correction for ‘A universal method for sensitive and cell-free detection of CRISPR-associated nucleases’ by Kurt J. Cox  In the original article, incorrect grant information from the Department of Energy was provided. The corrected Acknowledgements section is provided below, with the correct grant number:This work was supported by the Burroughs Wellcome Fund (Career Award at the Scientific Interface to A. C.), DARPA (Brdi N66001-17-2-4055 to A. C.), NIH (1R21AI126239-01 to A. C.), Army Research Office award W911NF1610586 (to A. C.), and by the Department of Energy through grant DE-SC0010595 to E. F., which supported the salary of H. K. K. S. This work is dedicated to Professor Ronald T. Raines on the occasion of his 60th birthday.The Royal Society of Chemistry apologises for these errors and any consequent inconvenience to authors and readers.


Mosaicism can be observed in karyotype analyses of amniotic fluid cells. Differentiating between true mosaicism and pseudomosaicism and determining mosaic proportions can help avoid misjudgments by doctors and effectively reduce mental and physical harm to pregnant women. However, the detection of mosaicism and mosaic proportions via karyotype analysis and fluorescence in situ hybridization (FISH) is extremely complex. We have developed a novel approach, “segmental duplication quantitative fluorescent PCR” (SD-QF-PCR), to detect mosaicism and mosaic proportions.In this study, twenty control samples and fourteen mosaic samples were tested by first-line karyotype analysis; by second-line karyotype analysis, SD-QF-PCR and FISH were used to reassess fetal sex chromosome mosaicism and mosaic proportions.Detection of the 20 control samples by second-line karyotype analysis via FISH and SD-QF-PCR showed normal and consistent results. Among the 14 mosaic samples, the numbers of samples showing true mosaicism and pseudomosaicism detected by the three methods were 6 and 8, respectively.Our study demonstrates that SD-QF-PCR can be used as a complementary method to traditional cytogenetic analysis of amniotic fluid mosaics and has clinical application value. However, mosaicism is often detected via karyotype analyses due to the long cultivation cycle of amniotic fluid cells and the complicated preparation process involved in such analyses.Fetal chromosomal abnormalities can be detected by amniotic fluid cell culture and karyotype analysis during the second trimester of pregnancy. Because of its detection scope and reliability, karyotype analysis has become the gold standard for detecting fetal chromosomal abnormalities. Pseudomosaicism, which is a culture artifact, is caused by maternal cell contamination or aberrations in exfoliated fetal cells during cultivation or the chromosome production process. TFM can severely affect fetal growth and mental development,,5 whereas pseudomosaicism leads to unnecessary prenatal interventions that cause significant mental and physical harm to pregnant women. Therefore, in current prenatal diagnoses, it is extremely important to accurately determine whether an observed mosaic represents TFM or pseudomosaicism to ensure that appropriate guidance and genetic counseling are provided.Mosaicism detected in prenatal diagnoses of amniotic fluid is classified as true fetal mosaicism (TFM) or pseudomosaicism. TFM is mainly caused by mitotic nondisjunction or chromosomal loss; it may also be caused by the absence of a chromosome in an individual daughter cell and its offspring due to chromatid retention in the anaphase stage of mitosis.,7 Test results should be further confirmed using second-line karyotype analysis, cord blood or other detection techniques such as FISH, and Doppler ultrasound should be utilized for systematic examination. If necessary, tests on multiple tissues should be conducted after the child is born, and postnatal follow-up should be enhanced.If fetal mosaicism is detected in the amniotic fluid using karyotype analysis, recommendations suggest careful treatment rather than termination of the pregnancy.,10 short tandem repeat analysis (STR-QF-PCR) and chromosomal microarray techniques. All of these diagnostic techniques have the advantage of rapid diagnosis. However, STR-QF-PCR cannot be used to assess mosaic proportions; thus, STR-QF-PCR cannot effectively reveal the extent of chromosome aberration during the cell culture process. FISH can effectively detect mosaic proportions but has the main drawbacks of being overly cumbersome and complex and requiring experienced technical staff. Chromosomal microarray technology can effectively detect mosaicism, but the cost of the instruments and reagents is extremely high, leading to a low level of acceptance of this approach in the developing world.With the development of molecular biology techniques, a number of diagnostic approaches have been utilized to diagnose fetal chromosome aneuploidy, such as FISH that can be used for the rapid diagnosis of aneuploidy. Upon our further study, we found that this quantitative approach was extremely accurate and stable and was therefore well suited for the detection and analysis of mosaicism and its proportions. Therefore, in this paper, we used the SD-QF-PCR technique to analyze amniotic fluid cell samples for mosaicism and compared this technique with FISH and traditional karyotyping, this approach allowed us to deeply investigate the clinical applicability and value of SD-QF-PCR for diagnosing chromosomal abnormalities.In our previous study, we developed a new detection method, “segmental duplication quantitative fluorescent PCR” (SD-QF-PCR),22.1This study was conducted in accordance with the principles expressed in the Declaration of Helsinki. The study protocol was approved by the Research Ethics Committee of Qinzhou Maternal and Child Health Hospital. Written informed consent was obtained from each participant for the collection of samples and subsequent analyses.2.2Twenty cases involving amniotic fluid samples with normal karyotypes and fourteen cases involving amniotic fluid samples with mosaicism were selected for this study. All 34 samples had undergone first-line amniotic fluid cell culture and karyotype analysis. Second-line amniotic fluid karyotype analysis was performed for validation.2.3X- and Y-chromosome centromere probes (GPMEDICAL) were used for FISH analyses of original amniotic fluid samples in all 34 included cases. In accordance with the manufacturer's instructions, 100 total cells were randomly counted for each sample, the types of sex chromosomes were determined based on the fluorescence signals of the X and Y chromosomes in cells, and mosaicism and mosaic proportions were determined using these fluorescence signals.2.4 and can be obtained from NCBI (http://www.ncbi.org/). The segmental duplications that can be used for QF-PCR detection and have diagnostic value refer to two similar sequences. The bases at both ends of similar sequences are identical for primer design, while the number of bases in the middle is different for copy number detection. Meanwhile, one of the similar sequences must be located on the target chromosome, and the other similar sequences, with different sizes, must be located on a chromosome other than the target chromosome.Segmental duplications are nearly identical DNA segments2.5Original amniotic fluid samples in all 34 cases were assessed via SD-QF-PCR. PCR amplification was performed using the Gene Amp PCR System 9700 (Applied Biosystems) in a total reaction volume of 25 μL containing 1× Reaction Master Mix (Tiangen Biotech), 10 ng genomic DNA and 0.5 μmol/L of each forward and reverse primer. The reaction mixture was preheated at 95°C for 3 min, followed by 28 cycles of 30 s at 95°C, 30 s at 60°C, and 30 s at 72°C and a final extension step at 72°C for 10 min. Approximately 1 μL of the PCR product was mixed with 24 μL of formamide and 1 μL of the GeneScan 500 Rox size standard (Applied Biosystems). The mixture was performed using a POP4 gel (Applied Biosystems) on the ABI 3130xl Genetic Analyzer (Applied Biosystems). GeneMapper ID Software v3.2 (Applied Biosystems) was used for the data analysis.2.6The ratio of the segmental duplications in two different chromosomes detected by SD-QF-PCR was converted to the mosaic proportion of different karyotypes, and this mosaic proportion was compared with that detected by first-line amniotic fluid karyotype analysis, with the second-line karyotype analysis and FISH analysis used to verify the accuracy and feasibility of the SD-QF-PCR method.33.1In this SD-QF-PCR experiment, two segmental duplications were used to detect numbers of sex chromosomes. Fragments from segmental duplications between chromosome 3 and chromosome X were used to calculate the copy number for the X chromosome, and segmental duplications between chromosome X and chromosome Y were used to detect the copy numbers for the X and Y chromosomes.Figure 3.2The result of SD-QF-PCR detection is the fluorescence ratio between the segmental duplications . We can only compare the result with other methods after converting the fluorescence ratio into the mosaic proportion. The calculation formula for conversion is as follows: Taking X:Y=1.174 Fig. C in the 3.3Thirty-four clinical amniotic fluid samples were detected using karyotype analysis, of which 20 control samples were obtained from individuals with the normal karyotype 46, XX or 46, XY. One sample was obtained from an individual with the karyotype 47, XXY/46, XY; 8 samples were obtained from individuals with the karyotype 45, X/46, XX; and 5 samples were obtained from individuals with the karyotype 45, X/46, XY. The partial karyotypes of the normal and mosaic chromosomes are shown in Figure 3.4All 34 samples were revalidated by second-line amniotic fluid karyotype analysis. The results of the 20 control samples were the same as those of the first-line analysis. In 14 suspected mosaic samples, the results of second-line amniotic fluid karyotype analysis indicated that 1 sample from an individual with the karyotype 47, XXY/46, XY; 3 samples from individuals with the karyotype 45, X/46, XX ; and 2 samples from individuals with the karyotype 45, X/46, XY . All of the mosaic proportions are presented in Table 3.5FISH probes were used to assess 14 amniotic fluid samples, of which 6 amniotic fluid samples were determined to be mosaics, and 8 amniotic fluid samples were of normal sex chromosome karyotype. The results were consistent with the results of the second-line amniotic fluid karyotype analysis. All of the mosaic proportions are presented in Table 3.6In normal female samples, the chromosome 3: chromosome X ratio was 1944: 1919 = 1.013, and chromosome Y was not amplified Fig. A. In norIn the SD-QF-PCR detection, 6 amniotic fluid samples were determined to be mosaics, and 8 amniotic fluid samples were of normal sex chromosome karyotype. The segmental duplication ratios and the karyotype proportions of the 14 amniotic fluid samples are presented in Table 4 Therefore, when a mosaic karyotype is observed in the amniotic fluid, the pregnancy should not be terminated immediately; instead, the karyotype results should be further validated via second-line amniotic fluid cell culture and karyotype analysis or cord blood karyotype analysis, or even FISH. If these additional assessments indicate TFM, tissues from the aborted fetus or the postnatal neonate can be evaluated to reach a final diagnosis.,17According to our results and those of other scholars, the main causes of mosaicism is maternal cell contamination or chromosomal aberrations produced during the in vitro cultivation of fetal exfoliated cells; thus, pseudomosaicism occurs more frequently than TFM. Among the current techniques, FISH,10 is an accurate means of testing for mosaicism. In this study, we developed a simpler and faster SD-QF-PCR approach to detect mosaicism and mosaic proportions. This technique can not only be used for the detection of amniotic fluid cells, but if it is applied to tissues from the chorionic villus, the aborted fetus or the postnatal neonate that cannot be cultured, this technique may be more advantageous than FISH or karyotyping.At present, second-line amniotic fluid karyotype analysis or cord blood karyotype analysis is the most common method for verifying first-line amniotic fluid results; however, second-line karyotype analysis also brings the possibility of pseudomosaicism. Therefore, if mosaicism occurs during amniotic fluid karyotyping, the best follow-up approach is to use the original amniotic fluid cells to determine whether a mosaic karyotype exists and thereby accurately differentiate between TFM and pseudomosaicism.The results of the karyotype analysis, FISH and SD-QF-PCR are shown in Table The results of 20 control samples from 3 methods indicated that all samples had normal sex chromosomes. In 14 amniotic fluid cell mosaic samples, the results of the second-line amniotic fluid karyotype analysis, FISH and SD-QF-PCR indicated that 6 samples had the TFM karyotype and 8 samples showed pseudomosaicism. Pseudomosaicism was found in 45, X/46, XX and 45, X/46, XY karyotypes, which is caused by aberrations in exfoliated fetal cells during cultivation or the chromosome production process. The results showed that all the three techniques can be used to identify TFM and pseudomosaicism.Although the three techniques can distinguish TFM and pseudomosaicism, the mosaic proportion detected by the three techniques is different in TFM. Since FISH technology is used to detect uncultured amniotic fluid cells, this technology can well reflect the mosaic proportion of original amniotic fluid cells. The karyotype analysis requires cell culture, and the attachment and growth of different cell types in the mosaic sample are different. Therefore, the results of the first-line karyotype analysis and the second-line karyotype analysis will be quite different (such as No. 2), which cannot accurately reflect the mosaic proportion of the original amniotic fluid cells. The SD-QF-PCR technique is similar to the FISH technique. Both techniques are used to detect uncultured amniotic fluid cells. The results in Table The SD-QF-PCR technology has very good development prospects, but there are still many areas that need further research. For example, although sex chromosome mosaicism occurs most, other chromosomes also have mosaicism. Therefore, it is necessary to further develop the detection system for other chromosomes. In addition, because the sample size is a little small, we cannot clarify the detection limit for the method. However, according to our current research, mosaicism is completely detectable for proportions above 10%. We will further improve this in the follow-up.5In conclusion, our study demonstrates that similar to FISH, SD-QF-PCR can be used as a complementary method to traditional cytogenetic analyses in the evaluation of amniotic fluid mosaics.Conceptualization: Zuqian Fan, Qian Yang, Lei Sun.Data curation: Zuqian Fan, Ju Long.Funding acquisition: Zhijian Pan, Lei Sun.Investigation: Zhijian Pan.Methodology: Ju Long.Project administration: Xunjin Weng.Resources: Xunjin Weng, Qian Yang.Software: Qiongying Fan.Supervision: Qiongying Fan.Validation: Guixian Lin.Writing – original draft: Lei Sun.Writing – review & editing: Lei Sun.


P. aeruginosa (PA), FDC utilizes TonB-dependent receptors (TBDR) PirA, PiuA, or PiuD to enter the periplasmic space. We recently reported a clinical PA isolate that developed elevated MICs to FDC associated with mutations in genes encoding TBDRs in the absence of prior exposure to FDC. In this study, we investigated the frequency of TBDR mutations not associated with cefiderocol exposure among clinical stains of PA recovered from 1999 to 2018 in a large hospital system in Houston, TX. Cefiderocol (FDC) is a novel siderophore cephalosporin that retains activity against MDR gram-negative bacteria. In PA were screened for mutations in TBDR pathways (pirA/pirRS and piuA/D) via whole genome sequencing. Strains with gene mutations predicted to significantly alter protein function  were selected for phenotypic characterization. PA PA01 and 4 clinical PA strains lacking changes in the TBDR genes served as controls. FDC susceptibility testing was performed on Mueller-Hinton agar by Kirby-Bauer disc diffusion (DD). Diameters were measured at 18 h and 48 h to assess for the emergence of colonies inside the zone of inhibition. Breakthrough colonies were isolated on cetrimide agar, and DD studies were performed to determine FDC susceptibility.A total of 212 clinical isolates of piuA (n=2) and pirR (n=2), and a frameshift mutation resulting in premature stop codon in pirR (n=9). DD showed that isolates with predicted changes in TBDRs had a significantly smaller diameter of inhibition, as compared to controls . Of the PiuA or PirR mutants, 3 of 13 demonstrated breakthrough colonies ; while none of the control specimens showed breakthrough colonies. Subcultures of isolated breakthrough colonies yielded more homogenous populations of PA with relatively lower DDs than the original strain . 6.1% of isolates (13/212) had preexisting mutations in the TBDR genes, including indels in Figure 1Cefiderocol disk diffusion diameters of P. aeruginosa isolates at (a) 18 hours growth and (b) 48 hours growth. P-values for student’s two-tailed t-test are given. Dotted lines represent cutoffs for intermediate and resistant per Clinical Laboratories and Standards Institute (CLSI) guidelines. ns, non-significant; TBDR, TonB dependent receptor.Figure 2Disk Diameter resistance phenotypes suggestive of heteroresistance among P. aeruginosa strains containing TBDR mutations (row 1) and their subsequent breakthrough colony subculture resistance phenotypes (row 2) at 48 hour time points.PA that predate the approval of FDC and are associated with the emergence of reduced susceptibility to FDC.Mutations in genes encoding TBDR are present in clinical isolates of Truc T. Tran, PharmD, Merck (Grant/Research Support) Cesar A. Arias, M.D., MSc, Ph.D., FIDSA, Entasis Therapeutics (Grant/Research Support)MeMed Diagnostics (Grant/Research Support)Merk (Grant/Research Support) William R. Miller, MD , Entasis Therapeutics (Scientific Research Study Investigator)Merck (Grant/Research Support) William R. Miller, MD , Entasis  Involved: Self): Scientific Research Study Investigator; Merck  Involved: Self): Grant/Research Support


Electroosmotic flow (EOF) has been widely used in various biochemical microfluidic applications, many of which use viscoelastic non-Newtonian fluid. This study numerically investigates the EOF of viscoelastic fluid through a 10:1 constriction microfluidic channel connecting two reservoirs on either side. The flow is modelled by the Oldroyd-B (OB) model coupled with the Poisson–Boltzmann model. EOF of polyacrylamide (PAA) solution is studied as a function of the PAA concentration and the applied electric field. In contrast to steady EOF of Newtonian fluid, the EOF of PAA solution becomes unstable when the applied electric field (PAA concentration) exceeds a critical value for a fixed PAA concentration (electric field), and vortices form at the upstream of the constriction. EOF velocity of viscoelastic fluid becomes spatially and temporally dependent, and the velocity at the exit of the constriction microchannel is much higher than that at its entrance, which is in qualitative agreement with experimental observation from the literature. Under the same apparent viscosity, the time-averaged velocity of the viscoelastic fluid is lower than that of the Newtonian fluid. Electroosmotic flow (EOF) uses electric field to control fluid motion, and has been widely used in various microfluidic and nanofluidic applications such as fluid pump , mixing Bello et al.  conducteRe). Such EOFs are time-dependent because of the nonlinear viscosity and elasticity of non-Newtonian fluids. Bryce and Freeman [Wi) .Recently, EOFs of non-Newtonian fluids have been reported to be time-dependent and show instabilities even at low Reynolds number τ=ηpc is governed by [For the OB model, the conformation tensor erned by ,(4)∂c∂tWi = 1; precise critical value also depends on the flow geometry) [c; and R is an orthogonal matrix with its columns being the eigenvalues of c. Equation (4) for the conformation tensor written in terms of Typically, numerical simulation of viscoelastic flow is difficult to converge for high Weissenberg number problem ,47. Compeometry) . Therefo becomes ,(6)∂Θ∂tensor ∇u .c is recovered from Then, the conformation tensor The total electric potential, Ψ=ϕExt+ψ , with ϕEequation  is used F is the Faraday’s constant ; and In the above, equation ,(9)∇2ϕEThe boundary conditions are given as follows :n denotes the normal unit vector on the surface.(1) At the Anode (edge AG in (2) At the Cathode (edge FL in (3) On the reservoir walls , an open-source viscoelastic EOF solver [Step 1.1. Compute steady state Step 1. Initialize the fields Step 2.1.1. Compute Step 2.1.2. Compute estimated velocity field Step 2.1.3. ompute pressure field Step 2.1.4. Correct the previously estimated velocity field using the correct pressure field.Step 2.1.5. Increase the inner iteration index u0==−0.11 V , and ε=6n 0.1 ms , and thex-component velocity profile at the center of the channel, and our numerical results (triangles) are in excellent agreement with the analytical result (line). Although the analytical solution is based on the Debey–Hückel approximation, we find that the numerical result also agrees well with the analytical solution when the zeta potential Afonso et al.  derived Newtonian fluid is investigated to provide the reference flow characteristic for the contraction geometry. For the PAA solution with different concentration x-axis. Additionally, the magnitude of the velocity, y-axis, For Newtonian fluids with various total viscosities, the EOF reaches a steady state under all conditions of the applied electric field strengths. There is no vortex occurring in the reservoirs and the constriction microchannel. The streamlines of Newtonian fluid show excellent symmetry about the x-axis. However, the streamlines near the solid walls of both reservoirs and in the outlet reservoir show insignificant change with time. Within 0.1 s, vortices continuously form and disappear within the inlet reservoir right before the entrance of the constriction microchannel. In For ever, Ko  did not on of Ko  under thon of Ko  experimeon of Ko  in termson of Ko , and we y-axis. Therefore, for Newtonian fluid, we have y-axis. For For Newtonian fluid, the EOF reaches a steady state, and the velocity magnitudes are symmetric about the  in Ko’s  experimey-axis. Velocity near the walls of the constriction microchannel is significantly higher than that at the centerline of the microchannel, and a local maximum occurs near the inlet/outlet corners of the constriction microchannel. However, in the EOF of Newtonian fluid, as shown in x-axis. The ratio of the maximum velocity magnitude near the channel walls to that at the centerline is 1.6. However, for PAA solution, due to the elastic instability, the velocity magnitude profile is asymmetric about the x-axis at y = 0). However, x at As PAA solution flows from the microchannel into the outlet reservoir, fluid velocity first decreases when fluid exits the microchannel and then increases in the outlet reservoir, as shown by the region marked with a circle in The generated elastic normal stress ometries ,61,62. Iometries ,64,65, aometries . Howeverometries . Althougx-axis and y-axis. As In order to study the effects of ns of Ko . Within es of Ko .x-axis. At the entrance of the microchannel, a slight increase of Since the flow velocity is time-dependent, we first calculate the cross-sectional average velocity over a period of We choose Under the considered condition of (1)When polyacrylamide (PAA) concentration (applied electric field) exceeds a critical value, the EOF of viscoelastic fluid becomes time-dependent with upstream vortices occurring in the inlet reservoir near the entrance of the constriction microchannel. In contrast, EOF of Newtonian fluid is always in a steady state without vortices.(2)For the viscoelastic EOF, significant polymer stress is induced near the entrance within the constriction and near the downstream lips of the constriction, causing the elastic instabilities of the viscoelastic EOF. The induced polymer stress is dramatically magnified with the increase of polymer concentration and applied electric field. However, the increase of polymer concentration shows a more significant enhancing effect on the polymer stress than the increase of applied electric field.(3)The EOF velocity of viscoelastic fluid within the constriction becomes temporally and spatially dependent. Near the exit of the constriction, due to the extrudate swell effect of the polymers, the velocity at the centerline first decreases at the exit followed by an increase in the outlet reservoir.(4)The velocity at the exit of the constriction is higher than that at the entrance of the constriction because of the formation of upstream vortices, which is in qualitative agreement with experimental observation obtained from the literature.(5)Under the same total viscosity and applied electric field, the velocity of Newtonian fluid is higher than that of viscoelastic fluid, which is attributed to the induced polymeric stress within the constriction. When the applied electric field is less than 300 V/cm, the Helmholtz–Smoluchowski velocity formula can predict the cross-sectional average velocity of viscoelastic fluid with PAA concentration up to 500 ppm, and the relative error is less than 5%. At a fixed PAA concentration, in general the relative error of the Helmholtz–Smoluchowski approximation increases with an increase in the applied electric field.Electroosmotic flow (EOF) of viscoelastic fluid through a 10:1:10 constriction microchannel is numerically investigated as functions of the applied electric field and the polymer concentration. In the current study, we neglect the effect of the polymer concentration on the zeta potential of the channel walls. Comparing to the EOF of Newtonian fluid, the following distinct results for viscoelastic EOF through a 10:1:10 constriction microchannel are obtained: