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Esther Veldhoen

and 9 more

Introduction Understanding the impact of scoliosis surgery on lung function is important for counseling patients about risks and benefits of surgery. We prospectively compared the trends in lung function test (LFT) results prior to and after scoliosis surgery in children with neuromuscular diseases, or dysmorphic syndromes. We hypothesized a stabilization. Methods We prospectively included children with neuromuscular or syndromic scoliosis able to perform LFTs. We studied (Forced) Vital Capacity ((F)VC), the ratio of Forced Expiratory Volume in 1 second (FEV1) and FVC, and Peak Expiratory Flow (PEF). Preoperative LFT results were compared with results 3-4 months after surgery. The mean monthly change in LFT results up to 2 years after surgery was compared with the preoperative natural history using linear mixed effects models. Results We included 43 patients. No significant change was observed in absolute values of (F)VC, FEV1/FVC and PEF prior to and after surgery. Median standardized VC, FVC and PEF decreased significantly after surgery from 59 to 58%, 60 to 51% and 61 to 53% respectively. The monthly rate of change in FVC was -0.13 % (95% CI -0.42 to 0.17) prior to surgery and -0.20% (95% CI -0.42 to 0.03) after surgery, mean difference -0.07 (95% CI -0.46 to 0.31; p=0.36). Conclusion No stabilization of lung function 3-4 months after scoliosis surgery was observed in children with neuromuscular and syndromic scoliosis with restrictive lung function disease. The effect of surgery on the rate of lung function decline remains inconclusive.

Cees Haringa

and 2 more

Compartment modeling (CM) is a well-known approach for computationally affordable, spatially-resolved hydrodynamic modeling of unit operations. Recent implementations use flow profiles based on CFD simulations, and several authors included microbial kinetics to simulate gradients in bioreactors. However, these studies relied on black-box kinetics, that do not account for intra-cellular changes and cell population dynamics in response to heterogeneous environments. In this paper, we report the implementation of a Lagrangian reaction model, where the microbial phase is tracked as a set of biomass-parcels, each linked with an intra-cellular composition vector and a structured reaction model describing their intra-cellular response to extracellular variations. A stochastic parcel tracking approach is adopted, in contrast to the resolved trajectories used in prior CFD implementations. A penicillin production process is used as a case-study. We show good performance of the model compared to full CFD simulations, both regarding the extra-cellular gradients and intra-cellular pool response, provided the mixing time in the CM matches the full CFD simulation; taking into account that the mixing time is sensitive to the number of compartments. The sensitivity of the model output towards some of the inputs is explored. The coarsest representative CM requires a few minutes to solve 80 hours of flow time, compared to approx. 2 weeks for a full Euler-Lagrange CFD simulation of the same case. This alleviates one of the major bottlenecks for the application of such CFD simulations towards analysis and optimization of industrial fermentation processes.

yi he chen

and 7 more

Background: Simultaneous atrial fibrillation (AF) catheter ablation and left atrial appendage closure (LAAC) is sometimes recommended for both rhythm control and stroke prevention. However, the advantages of intracardiac echocardiography (ICE) guidance for this combined procedure have been scarcely reported. To evaluate the clinical outcomes and safety of ICE guided LAAC within a zero-fluoroscopy catheter ablation procedure. Methods and Results:From April 2019 to April 2020, 56 patients with symptomatic AF underwent concomitant catheter ablation and LAAC. ICE with a multi-angled imaging protocol mimicking the TEE echo windows was used to guide LAAC. Successful radiofrequency catheter ablation and LAAC was achieved in all patients. Procedure-related adverse event rate was 3.6%. During the 12-month follow-up, 77.8% of patients became free of arrhythmia recurrences and oral anticoagulants were discontinued in 96.4% of patients. No ischemic stroke occurred despite two cases of device-related thrombosis versus an expected stroke rate of 4.8% based on the CHA2DS2-VASc score. The overall major bleeding events rate was 1.8%, which represented a relative reduction of 68% versus an expected bleeding rate of 5.7% based on the HAS-BLED score of the patient cohort. The incidence of iatrogenic atrial septal defect secondary to a single transseptal access dropped from 57.9% at 2 months to 4.2% at 12 months TEE follow-up. Conclusion:The combination of catheter ablation and LAAC under ICE guidance was safe and effective in AF patients with high stroke risk. ICE with our novel protocol was technically feasible for comprehensive and systematic assessment of device implantation.

Jin Yu

and 7 more

Object: Investigate the value of transesophageal echocardiography (TEE) in perimembranous ventricular septal defect (PmVSD) closure via a left parasternal ultra‐minimal trans intercostal incision in children. Methods: From January 2015 and December 2020, 212 children with PmVSD were performed device occlusion via an ultraminimal intercostal incision. TEE is used throughout the perioperative period, including TEE assessment, TEE-guided localization of the puncture site, TEE guidance. All patients were followed up using transthoracic echocardiography for over 6 months. Results: A total of 207 cases successfully occluded, the successful rate was 97. 64%. one hundred and forty-five patients had single orifice, and 62 patients had multiple orifices in the AMS. During the operation, the surgeon readjusted the device or replaced the larger device in 17 cases. After operation, there were 19 cases of slight residual shunts, 13 cases of pericardial effusion and 4 cases of pleural effusion. And all were back to normal during the 4- month follow-up period. Mild mitral regurgitation was presented in 1 patient and remained the same during the follow-up period. No other complications were found. Conclusions: TEE was used to evaluate and determine the defect in PmVSDs with an concentric occluder via a left parasternal ultra‐minimal trans intercostal incision. TEE guidance and immediate postoperative efficacy evaluation are of great value, which can effectively guide the treatment of PmVSD occlusion.
Objectives Pulmonary atresia (PA) with ventricular septal defect (VSD) and systemic-pulmonary collateral arteries (SPCA’s) has a variable anatomy with regard to the pulmonary vasculature, asking for an individualized surgical treatment. A protocol was applied consisting of staged unifocalization and correction. Methods Since 1989 39 consecutive patients were included (median age at first operation 13 months). In selected cases a central aorto-pulmonary shunt was performed as first procedure. Unifocalization procedures were performed through a lateral thoracotomy. Correction consisted of shunt takedown, VSD closure and interposition of an allograft between the right ventricle and the reconstructed pulmonary artery. Postoperatively and at follow up echocardiographic data were obtained. Results In 39 patients 66 unifocalization procedures were performed. Early mortality was 5%. Seven patients were considered not suitable for correction, four of them died. One patient is awaiting further correction. Correction was done successfully in 28 patients. Operative mortality was 3% and late mortality 11%. Median follow-up after correction was 19 years. Eleven patients needed homograft replacement. Freedom from conduit replacement was 88%, 73% and 60% at 5, 10 and 15 years respectively. Right ventricular function was reasonable or good in 75 % of the patients. Conclusions After complete unifocalization 30/37 patients (81%) were considered correctable. The main reasons for palliative treatment without correction were pulmonary hypertension and/or inadequate outgrowth of pulmonary arteries. Staged approach of PA, VSD and SPCA’s results in adequate correction and good functional capacity. RV function after correction remains reasonable or good in the majority of patients.

Xiaohua Huang

and 2 more

Deuterated water has been applied in hydrogeological tracer tests in recent years. However, there is a contradiction about the conservativeness of artificial deuterium (D/2H). In this study, what circumstances HDO behaved truly conservatively were investigated through laboratory-scale experiments via comparing the widely used tracer chloride (Cl-). And reasons for the non-conservativeness of HDO were discussed comprehensively for the first time. In addition, the advection-dispersion equation (ADE) and dual-domain mass transfer (DDMT) equation were employed to describe the breakthrough curves (BTCs) of tracers. HDO behaved conservatively when it transported in the porous media with high permeability (approximately K > 1m/d), and ADE could describe BTCs successfully. While hysteresis effect of HDO expressed in the media with low permeability. And the lower the permeability of the porous media, the stronger the hysteresis effect. DDMT was more suitable for demonstrating BTCs in low permeability media. Hydrogen bonds between HDO and H2O, the isotopic exchange effect, and the dual-domain model of the media all could lead to the hysteresis effect. The retardation factor (R = 1.712) was used to describe transporting behaviors of HDO in clay firstly. And the threshold hydraulic conductivity (Kcr) and the proportion of immobile regions of HDO were greater than that of Cl-, while dispersion coefficients of HDO were smaller. These could provide further considerations for using deuterium in hydrogeological tracer tests.

Weigang Tang

and 1 more

Flow regimes are critical for determining physical and biological processes in rivers, and their classification and regionalization traditionally seeks to link patterns of flow to physiographic, climate and other information. There are many approaches to, and rationales for, catchment classification, with those focused on streamflow often seeking to relate a particular response characteristic to a physical property or climatic driver. Rationales include such topics as Prediction in Ungauged Basins (PUB), helping with experimental approaches, and providing guidance for model selection in poorly understood hydrological systems. While scale and time are important considerations for classification, the Annual Daily Hydrograph (ADH) is a first-order easily visualized integrated expression of catchment function, and over many years is a distinct hydrological signature. In this study, we use t-SNE, a state-of-the-art technique of dimensionality reduction, to classify 17110 ADHs for 304 reference catchments in mountainous Western North America. t-SNE is chosen over other conventional methods of dimensionality reduction (e.g. PCA) as it presents greater separability of ADHs, which are projected on a 2D map where the similarities are evaluated according to their map distance. We then utilize a Deep Learning encoder to upgrade the non-parametric t-SNE to a parametric approach, enhancing its capability to address ‘unseen’ samples. Results showed that t-SNE was an effective classifier as it successfully clustered ADHs of similar flow regimes on the 2D map. In addition, many compact clusters on the 2D map in the coastal Pacific Northwest suggest information redundancy in the local hydrometric network. The t-SNE map provides an intuitive way to visualize the similarity of high-dimensional data of ADHs, groups catchments with like characteristics, and avoids the reliance on subjective hydrometric indicators.

Jing Wei

and 3 more

Switching to a new host plant is a driving force for divergence and speciation in herbivorous insects. This process of incorporating a novel host plant into the diet may require a number of adaptations in the insect herbivores that allow them to consume host plant tissue that may contain toxic secondary chemicals. As a result, herbivorous insects are predicted to have evolved efficient ways to detoxify major plant defenses and increase fitness by either relying on their own genomes or by recruiting other organisms such as microbial gut symbionts. In the present study we used parallel meta-transcriptomic analyses of Altica flea beetles and their gut symbionts to explore the contributions of beetle detoxification mechanisms versus detoxification by their gut consortium. We compared the gut meta-transcriptomes of two sympatric Altica species that feed exclusively on different host plant species as well as their F1 hybrids that were fed one of the two host plant species. These comparisons revealed that gene expression patterns of Altica are dependent on both beetle species identity and diet. The community structure of gut symbionts was also dependent on the identity of the beetle species, and the gene expression patterns of the gut symbionts were significantly correlated with beetle species and plant diet. Some of the enriched genes identified in the beetles and gut symbionts are involved in the degradation of secondary metabolites produced by plants, suggesting that Altica flea beetles may use their gut microbiota to help them feed on and adapt to their host plants.


and 6 more

Snow density is one of the essential properties to describe snowpack characteristics. To obtain the spatial variability of snow density and estimate it accurately in different periods of snow season still remain as challenges, particularly in the mountains. This study analyzed the spatial variability of snow density with in-situ measurements in three different periods (i.e. accumulation, stable, melt period) of snow seasons 2017/2018 and 2018/2019 in the middle Tianshan Mountains, China. The performance of multiple linear regression model (MLR) and three machine learning models (i.e. Random Forest (RF), Extreme Gradient Boosting (XGB) and Light Gradient Boosting Machine (LGBM)) to simulate snow density has been evaluated. It was found that the snow density in melt period (0.27 g cm-3) was generally greater than that in stable (0.20 g cm-3) and accumulation period (0.18 g cm-3), and the spatial variability of snow density in melt period was slightly smaller than that in other two periods. The snow density in mountainous areas was generally higher than that in plain or valley areas, and snow density increased significantly (p < 0.05) with elevation in the accumulation and stable periods. Besides elevation, latitude and ground surface temperature also had critical impacts on the spatial variability of snow density in the middle Tianshan Mountains, China. In this work, the machine learning model, especially RF model, performed better than MLR on snow density simulation in three periods. Compared with MLR, the determination coefficients of RF promoted to 0.61, 0.51 and 0.58 from 0.50, 0.1 and 0.52 in accumulation period, stable period and melt period respectively. This study provide a more accurate snow density simulation method for estimating regional snow mass and snow water equivalent, which allows us to achieve a better understanding of regional snow resources.

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Sangjun Yoo

and 7 more

Introduction: We assessed the effects of preoperative bladder compliance on the long-term functional outcomes, especially focused on postoperative storage symptom changes, after laser prostatectomy. Materials and Methods: From January 2008 to March 2014, 1608 men who underwent laser prostatectomy, including holmium laser enucleation or photo-vaporization of the prostate, were included in the analysis. We divided patients into 3 groups according to bladder compliance on a baseline urodynamic study: < 12.5; 12.5–25.0; ≥25 mL/cm H2O. A multivariable analysis was performed to determine the impact of bladder compliance on long-term functional outcomes after laser prostatectomy. Results: Bladder compliance was less than 12.5 ml/cm H2O in 50 (3.1%), 12.5-25 ml/cm H2O in 232 (14.4%) patients. As bladder compliance decreased, the baseline International Prostate Symptom (I-PSS) total score and storage sub-score were increased; the voiding sub-score remain unchanged. At postoperative 36 months, improvements in the I-PSS total score and storage sub-score were significantly higher in < 12.5 mL/cm H2O group compared to other groups, although those were equivalent at postoperative 1 and 12 months. On the multivariable analysis, decreased bladder compliance < 12.5 mL/cm H2O was significantly associated with superior improvement in storage sub-score at postoperative 36 months, although it was not associated with voiding sub-score. Conclusion: In patients with preoperative bladder compliance < 12.5 mL/cm H2O, storage symptoms could be further improved at 36 months after laser prostatectomy compared to others. Thus, laser prostatectomy could be a considerable treatment option for patients with severely decreased bladder compliance

Colum Keohane

and 6 more

Abstract Objective To determine whether the introduction of a one-stop see and treat clinic offering early reflux ablation for Venous Leg Ulcer (VLU) patients in July 2016 has affected rates of unplanned inpatient admissions due to venous ulceration. Design Review of inpatient admission data and analysis of related costs. Materials The Hospital Inpatient Enquiry collects data from acute public hospitals in Ireland on admissions and discharges, coded by diagnosis and acuity. This was the primary source of all data relating to admissions and length of stay. Costs were calculated from data published by the Health Service Executive in Ireland on average costs per inpatient stay for given diagnosis codes. Methods Data were collected on admission rates, length of stay, overall bed day usage, and costs across a four-year period; the two years since the introduction of the rapid access clinic, and the two years immediately prior as a control. Results 218 patients admitted with VLUs accounted for a total of 2,529 inpatient bed-days, with 4.5(2-6) unplanned admissions, and a median hospital stay of 7(4-13) days per month. Median unplanned admissions per month decreased from 6(2.5-8.5) in the control period, to 3.5(2-5) after introduction of the clinic p=.040. Bed-day usage was significantly reduced from median 62.5(27-92.5), to 36.5(21-44) bed-days per month (p=.035), though length of stay remained unchanged (p=.57). Cost of unplanned inpatient admissions fell from median \euro33,336.25(\euro14,401.26-\euro49,337.65) per month to \euro19,468.37(\euro11,200.98-\euro22,401.96) (p=.03). Conclusions Admissions for inpatient management of VLUs have fallen after beginning aggressive endovenous treatment of venous reflux in a dedicated one-stop see-and-treat clinic for these patients. As a result, bed-day usage has also fallen, leading to cost savings.

Mürşide Zengin

and 2 more

Aim: The aim of this study was to determine the anxiety levels of parents with children aged 3-6 years due to the Coronavirus Disease-2019 (COVID-19) pandemic and to examine the effects of Solution-Focused Support Program (SFSP) applied to parents with high level of anxiety. Methods: The study was conducted as a parallel-group, randomized controlled design. The sample of the study consisted of 77 parents who were randomly assigned to the experimental and control groups (control group n = 40; intervention group n = 37). One session of online SFSP was applied to the intervention group each week and 4 sessions were applied in total. No intervention was applied to the control group. The data were collected using introductory information form and State-Trait Anxiety Inventory (STAI). Statistical Package for the Social Sciences (SPSS) programme and Analysis of Moment Structures (AMOS) 23 application were used in the analysis of the data.  Structural Equation Modeling (SEM) was used to examine a hypothesized model that SFSP has both direct and indirect effects on anxiety levels of parents.Results: The state and trait anxiety mean scores of the intervention group decreased compared to the pre-intervention mean scores after the implemented programme. While this difference between state anxiety scores was statistically significant (p≤ .001), the difference between trait anxiety scores was not statistically significant (p> .05). There was no statistically significant difference between the pre-test and post-test STAI total scores of the control group.Conclusions: In the study, it has been found that SFSP applied to parents with high level of anxiety is an effective method in reducing the state anxiety levels of parents. Clinical trial number: NCT04609722 (Registration date: 30.10.2020)

Mohammed Al-Sadawi

and 7 more

Abstract: Background: This meta-analysis assessed the relationship between Obstructive Sleep Apnea (OSA) and echocardiographic parameters of diastolic dysfunction (DD), which are used in the assessment of Heart Failure with Preserved Ejection Fraction (HFpEF). Methods: We searched the databases including Ovid MEDLINE, Ovid Embase Scopus, Web of Science, Google Scholar, and EBSCO CINAHL from inception up to December 26th, 2020. The search was not restricted to time, publication status or language. Comparisons were made between patients with OSA, diagnosed in-laboratory polysomnography (PSG) or home sleep apnea testing (HSAT), and patients without OSA in relation to established markers of diastolic dysfunction. Results: Primary search identified 2512 studies. A total of 18 studies including 2509 participants were included. The two groups were free of conventional cardiovascular risk factors. Significant structural changes were observed between the two groups. Patients with OSA exhibited greater LAVI (3.94 CI [0.8, 7.07]; p=0.000) and left ventricular mass index (11.10 CI [2.56,19.65]; p=0.000) as compared to control group. The presence of OSA was also associated with more prolonged DT (10.44 ms CI [0.71,20.16]; p=0.04), IVRT (7.85 ms CI[4.48, 11.22]; p=0.000), and lower E/A ratio (-0.62 CI [-1,-0.24]; p=0.001) suggestive of early DD. The E/e’ ratio (0.94 CI[0.44, 1.45]; p=0.000) was increased. Conclusion: An association between OSA and echocardiographic parameters of DD was detected that was independent of conventional cardiovascular risk factors. OSA may be independently associated with DD perhaps due to higher LV mass. Investigating the role of CPAP therapy in reversing or ameliorating diastolic dysfunction is recommended.

Hans Fangohr

and 2 more

Guest Editors’ IntroductionNotebook interfaces – documents combining executable code with output and notes – first became popular as part of computational mathematics software such as Mathematica and Maple. The Jupyter Notebook, which began as part of the IPython project in 2012, is an open source notebook that can be used with a wide range of general-purpose programming languages.Before notebooks, a scientist working with Python code, for instance, might have used a mixture of script files and code typed into an interactive shell. The shell is good for rapid experimentation, but the code and results are typically transient, and a linear record of everything that was tried would be long and not very clear. The notebook interface combines the convenience of the shell with some of the benefits of saving and editing code in a file, while also incorporating results, including rich output such as plots, in a document that can be shared with others.The Jupyter Notebook is used through a web browser. Although it is often run locally, on a desktop or a laptop, this design means that it can also be used remotely, so the computation occurs, and the notebook files are saved, on an institutional server, a high performance computing facility or in the cloud. This simplifies access to data and computational power, while also allowing researchers to work without installing any special software on their own computer: specialized research software environments can be provided on the server, and the researcher can access those with a standard web browser from their computer.These advantages have led to the rapid uptake of Jupyter notebooks in many kinds of research. The articles in this special issue highlight this breadth, with the authors representing various scientific fields. But more importantly, they describe different aspects of using notebooks in practice, in ways that are applicable beyond a single field.We open this special issue with an invited article by Brian Granger and Fernando Perez – two of the co-founders and leaders of Project Jupyter. Starting from the origins of the project, they introduce the main ideas behind Jupyter notebooks, and explore the question of why Jupyter notebooks have been so useful to such a wide range of users. They have three key messages. The first is that Notebooks are centered around the humans using them and building knowledge with them. Next, notebooks provide a write-eval-think loop that lets the user have a conversation with the computer and the system under study, which can be turned into a persistent narrative of computational exploration. The third idea is that Project Jupyter is more than software: it is a community that is nourished deliberately by its members and leaders.The following five articles in this special issue illustrate the key features of Project Jupyter effectively. They show us a small sample of where researchers can go when empowered by the tool, and represent a range of scientific domains.Stephanie Juneau et al. describe how Jupyter has been used to ‘bring the compute to the data’ in astrophysics, allowing geographically distributed teams to work efficiently on large datasets. Their platform is also used for education & training, including giving school students a realistic taste of modern science.Ryan Abernathey et al. , of the Pangeo project, present a similar scenario with a focus on data from the geosciences. They have enabled analysis of big datasets on public cloud platforms, facilitating a more widely accessible ‘pay as you go’ style of analysis without the high fixed costs of buying and setting up powerful computing and storage hardware. Their discussion of best practices includes details of the different data formats required for efficient access to data in cloud object stores rather than local filesystems.Marijan Beg et al. describe features of Jupyter notebooks and Project Jupyter that help scientists make their research reproducible. In particular, the work focuses on the use of computer simulation and mathematical experiments for research. The self-documenting qualities of the notebook—where the response to a code cell can be archived in the notebook—is an important aspect. The paper addresses wider questions, including use of legacy computational tools, exploitation of HPC resources, and creation of executable notebooks to accompany publications.Blaine Mooers describes the use of a snippet library in the context of molecular structure visualization. Using a Python interface, the PyMOL visualization application can be driven through commands to visualize molecular structures such as proteins and nucleic acids. By using those commands from the Jupyter notebook, a reproducible record of analysis and visualizations can be created. The paper focuses on making this process more user-friendly and efficient by developing a snippet library, which provides a wide selection of pre-composed and commonly used PyMOL commands, as a JupyterLab extension. These commands can be selected via hierarchical pull-down menus rather than having to be typed from memory. The article discusses the benefits of this approach more generally.Aaron Watters describes a widget that can display 3D objects using webGL, while the back-end processes the scene using a data visualization pipeline. In this case, the front-end takes advantage of the client GPU for visualization of the widget, while the back-end takes advantage of whatever computing resources are accessible to Python.The articles for this special issue were all invited submissions, in most cases from selected presentations given at JupyterCon in October 2020. Each article was reviewed by three independent reviewers. The guest editors are grateful to Ryan Abernathey, Luca de Alfaro, Hannah Bruce MacDonald, Christopher Cave-Ayland, Mike Croucher, Marco Della Vedova, Michael Donahue, Vidar Fauske, Jeremy Frey, Konrad Hinsen, Alistair Miles, Arik Mitschang, Blaine Mooers, Samual Munday, Chelsea Parlett, Prabhu Ramachandran, John Readey, Petr Škoda and James Tocknell for their work as reviewers, along with other reviewers who preferred not to be named. The article by Brian Granger and Fernando Perez was invited by the editor in chief, and reviewed by the editors of this special issue.Hans Fangohr is currently heading the Computational Science group at the Max Planck Institute for the Structure and Dynamics of Matter in Hamburg, Germany, and is a Professor of Computational Modelling at the University of Southampton, UK. A physicist by training, he received his PhD in Computer Science in 2002. He authored more than 150 scientific articles in computational science and materials modelling, several open source software projects, and a text book on Python for Computational Science and Engineering. Contact him at hans.fangohr@mpsd.mpg.deThomas Kluyver is currently a software engineer at European XFEL. Since gaining a PhD in plant sciences from the University of Sheffield in 2013, he has been involved in various parts of the open source & scientific computing ecosystems, including the Jupyter & IPython projects. Contact him at thomas.kluyver@xfel.euMassimo Di Pierro is a Professor of Computer Science at DePaul University. He has a PhD in Theoretical Physics from the University of Southampton and is an expert in Numerical Algorithms, High Performance Computing, and Machine Learning. Massimo is the lead developer of many open source projects including web2py, py4web, and pydal. He has authored more than 70 articles in Physics, Computer Science, and Finance and has published three books. Contact him at

Jumpei Ogura

and 9 more

Introduction: Methicillin-resistant Staphylococcus aureus (MRSA) infection has a significant clinical impact on both pregnant women and neonates. The aim of this study was to accurately assess the vertical transmission rate of MRSA and its clinical impacts on both pregnant mothers and neonates.Material and Methods: We conducted a prospective observational cohort study of 898 pregnant women who were admitted to our department and 905 neonates from August 2016 to December 2017. MRSA was cultured from  nasal and vaginal samples taken from the mothers at enrollment and from nasal and umbilical surface swabs taken from neonates at the time of delivery. We examined the vertical transmission rate of MRSA in mother-neonate pairs. We used multivariable logistic regression to identify risk factors for maternal MRSA colonization and maternal/neonatal adverse outcomes associated with maternal MRSA colonization.Results: The prevalence of maternal MRSA colonization was 6.1% (55 out of 898) at enrollment. The independent risk factors were multiparity and occupation (healthcare provider) (OR: 2.35, 95% CI: 1.25-4.42, OR: 2.58, 95% CI: 1.39-4.79, respectively). The prevalence of neonatal MRSA colonization at birth was 12.7% (7 out of 55 mother-neonate pairs) in the maternal MRSA-positive group, whereas it was only 0.12% (one out of 843 pairs) in the maternal MRSA-negative group (OR: 121, 95% CI: 14.6-1000). When maternal vaginal samples were MRSA positive, vertical transmission was observed in four out of nine cases (44.4%) in this study. Skin and soft tissue infections (SSTIs) developed more frequently in neonates in the maternal MRSA-positive group than in the MRSA-negative group (OR: 7.47, 95% CI: 2.50-22.3).Conclusions: The prevalence of MRSA in pregnant women was approximately 6%. Vertical transmission caused by maternal vaginal MRSA colonization was observed in four out of nine cases (44.4%). Although our study includes limited number of maternal MRSA positive cases, the vertical transmission of MRSA may occur in up to 44% of neonates of mothers with vaginal MRSA colonization. Maternal MRSA colonization may associate with increased development of SSTIs in neonates via vertical transmission.
Many societal opportunities and challenges, both current and future, are either inter- or transdisciplinary in nature. Focus and action to cut across traditional academic boundaries has increased in research and, to a less extent, teaching. One successful collaboration has been the augmentation of fields within the Humanities, Social Sciences, and Arts by integrating complementary tools and methods originated from STEM. This trend is gradually materializing in formal undergraduate and secondary education.The proven effectiveness of Jupyter notebooks for teaching and learning STEM practices gives rise to a nascent case for education seeking to replicate this interdisciplinary design to adopt notebook technology as the best pedagogical tool for this job. This article presents two sets of data to help argue this case.The first set of data demonstrates the art of the possible. A sample of undergraduate and secondary level courses showcases existing or recent work of educational stakeholders in the US and UK who are already pioneering instruction where computational and data practices are integrated into the study of the Humanities, Social Sciences, and Arts, with Jupyter notebooks chosen as a central pedagogical tool. Supplementary data providing an overview of the types of technical material covered by each course syllabi further evidences what interdisciplinary education is perceived to be or is already feasible using this Jupyter technology with student audiences of these levels.The second set of data provides more granular, concrete insight derived from user experiences of a handful of the courses from the sample. Four instructors and one student describe a range of pedagogical benefits and value they attribute to the use of Jupyter notebooks in their course(s).In presenting this nascent case, the article aims to stimulate the development of Jupyter notebook-enabled, computational data-driven interdisciplinary education within undergraduate and secondary school programs.

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