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Regina Baucom

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Resistance evolution, from genetic mechanism to ecological contextRegina S. Baucom1, Veronica Iriart2, Julia Kreiner3, and Sarah Yakimowski41Ecology and Evolutionary Biology Department, University of Michigan, Ann Arbor, Michigan, USA2Department of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, USA3Biodiversity Research Centre & Department of Botany, The University of British Columbia, Vancouver, BC V6T 1Z44Department of Biology, Queen’s University, Kingston, ON K7L 3N6CorrespondenceRegina S. Baucom, Ecology and Evolutionary Biology Department, University of Michigan, Ann Arbor, Michigan, 48109.Email: rsbaucom@umich.edu*Authors contributed equallyPesticide use by humans has induced strong selective pressures, reshaping evolutionary trajectories, ecological networks, and even influencing ecosystem dynamics. The evolution of pesticide resistance across weeds, insects, and fungi often leads to negative impacts on both human health and the economy while concomitantly providing excellent systems for studying the process of evolution. In fact, the study of pesticide resistance has been a feature of evolutionary biology since the Evolutionary Synthesis, with Dobzhansky noting in his book The Genetics and Origins of Species (1937) that cyanide resistance in the California red scale constituted the “best proof of the effectiveness of natural selection yet obtained”. Following the pioneering work of James Crow and others in the 1950’s—which greatly expanded our knowledge of the genetics underlying adaptation—the study of pesticide resistance has shed light on a variety of topics, such as the repeatability of phenotypic evolution across the landscape, ‘hotspots’ of evolution across the genome, and information on the number and type of genetic solutions that populations may employ to strong selection pressures.Landscape level approaches have come to the forefront over the last 20 years of resistance evolution research, often taking advantage of the fact that replicated populations of the same species are exposed to the same pesticide. Further, the resistance evolution field is turning more attention to the ecological context within which resistance evolution occurs, likely stemming, at least in part, from an historical focus on fitness costs (Cousens & Fournier-Level 2018; Baucom 2019). This special feature, ‘Resistance evolution, from genetic mechanism to ecological context’ in Molecular Ecology captures the current state of resistance evolution with contributions broadly addressing the question ‘What has the rapid evolution of pesticide resistance taught us about genome dynamics and adaptation as well as the ecological context within which resistance evolution occurs?’ Below, we contextualize the manuscripts in this special issue that provide insight into the state of the art investigations of resistance evolution across various species of insects, weeds and fungi.
Reintroduction failure after undergoing oral immunotherapy or oral food challenges with cooked eggTo the editor,Food allergy has increased in recent decades currently affecting almost 6% of the european pediatric population (1). Egg is the second leading cause in food allergy (1) and in anaphylactic food reactions (2) among preschool-aged children in Europe. Recent studies have suggested a persistent tendency for egg allergy, estimating that less than 50% of these children can tolerate it by 2 years of age (3). However, up to 70% of egg-allergic children tolerate cooked egg (4). Some studies suggest that regular consumption of cooked egg in these children might increase their probability of tolerating egg in any presentation in the future (5, 6). In the past decades, complete egg avoidance was the recommended treatment in egg allergic patients. This recommendation has an important impact in quality of life of the patients and their families and does not guarantee the prevention of severe reactions due to accidental ingestion of even small amounts of the offending food (2, 7). Oral immunotherapy (OIT) for persistent egg allergy has emerged as an alternative therapy to egg avoidance. Tolerance can be induced by the administration of different egg products and maintained by the regular ingestion of egg several times per week, indefinitely.Previous retrospectives studies had shown, that around 25% of children with negative oral food challenges OFC) did not reintroduce the food at home with a lower successful introduction rate for peanut (32-60%) than for milk (10-22%) or egg (13-29%) (8-10). Aversion and refusal of the food, reactions at home after being tolerated in hospital and fear of reactions were the most reported reasons for peanut reintroduction failure (8-10).As the type of food significantly influences the rate of non-adherence to its regular consumption (9), its causes might be also different depending on the food involved. The aim of our study was to analyze the leading causes of lack of adherence to the regular ingestion of cooked egg after undergoing OIT or an OFC with cooked egg.Egg allergic patients among 2-17 years old, not following the recommendation of maintaining the intake of three eggs per week after undergoing OIT or OFC with cooked egg, were prospectively recruited from the Allergy Service of Hospital General Universitario Gregorio Marañón (Madrid) and Clínica Universidad de Navarra (Pamplona) between January 2019 and May 2020. The patients or their legal representatives, in the case of children under 12 years, fulfilled a questionnaire (supplemental file) regarding demographic and clinical information and the causes of lack of adherence or abandonment of regular intake of cooked egg. The questionnaire was also published in Twitter (Twitter Inc, San Francisco, Calif) and anonymously fulfilled. Qualitative variables were expressed in percentages and quantitative variables were expressed as median and interquartile range (IQR). The study was approved by the Ethics Committee for Investigation of both participating hospitals.Twenty patients were included in the study [55% female; median age: 10.7 years (IQR: 9-16.3)]. Fifteen (75%) were recommended to maintain regular intake of cooked egg after OIT and 5 (20%) after OFC. Patient´s diagnosis of egg allergy was performed by a median age of 14.5 months (IQR: 11-16 months). Median time of egg avoidance before OFC or OIT with cooked egg was 6.1 years (IQR: 3.6-9.4 years).Four (20%) patients referred a frequency intake of two cooked eggs weekly, seven (35%) referred the ingestion of one egg weekly and nine (45%) only consumed breaded/floured foods with egg. The causes of lack of adherence to the regular intake of cooked egg are summarized in the figure. Most of the patients reported poor compliance as they did not like the taste (85%), the texture (70%) or the smell (65%) of egg. Other causes of lack of adherence were being tired of eating the food in the same cooking presentation (55%), the difficulty to find a variety of recipes (50%), reactions at home after tolerance assessment by OFC or OIT (35%), considering the recommended intake excessively frequent (25%), fear of having a reaction (20%), forgetting (20%) and rejection of the appearance of the egg (10%). One out of 20 patients (5%) reported lack of adherence due to interference with other activities such as sports, other food allergies and living with egg allergic relatives.According to our results, the most frequent cause for which patients decreased or stopped the regular ingestion of cooked egg is aversion of the food (related to the organoleptic characteristics of the egg: taste, texture, and/or smell) which is in accordance with other studies performed with other allergens (9, 10). The second cause of poor adherence in our study, was the lack of variety in their cooking preparation which has not been observed in other studies with other foods.While in the case of peanuts, fear of having a reaction is among the first three causes of reintroduction failure (10), this does not seem to be an important cause in the case of egg, being the fifth cause referred by the patients in our study. We therefore believe that it is important to analyze the causes of lack of adherence to regular consumption of a food after having verified its tolerance, depending on the food and the type of presentation in which it is indicated to consume since they seem different and therefore the possible measures on which to act.Our study has some limitations, as the relative small sample group. Time spam between food challenge and completion of the questionnaire is wide and probably those children fulfilling the questionnaire closer to the challenge, did it more correctly. Moreover, we do not have data on the exact timing of failure. The questionnaire is not validated, thus we cannot rule out that the content and way of asking may have influenced the results of our study. In addition, the inclusion criteria in those patients who fullfilled the questionnaire via Twitter could not be verified.In our opinion, strategies to promote regular cooked egg consumption such as providing a variety of recipes for safe consumption with masked egg, suggesting practical recommendations to favor the regular intake or emphasizing in patient education regarding the importance of maintaining the regular consumption of the food could be useful to facilitate compliance in these patients and maintain the acquired tolerance.

BRUCE S A IESHA

and 3 more

Objectives To study the patterns of glycemic status in response to steroid administered to women with risk of preterm delivery between 24 weeks and 36 weeks 6 days of gestation in normoglycemic subjects and to evaluate if maternal characteristics predicted the development of hyperglycemia and if Insulin was necessary in the glycemic management Design : longitudinal study Participants : 76 antenatal women, normoglycemic status between 24 weeks and 36 week 6 days of gestation Methods : Antenatal women who screened negative for Gestational Diabetes Mellitus by 75 gm GTT who received Injection Betamethasone for risk of preterm delivery . Fasting and Postprandial blood sugar levels were recorded from day 1 to 7 after steroid administration. Results Forty seven out of seventy six patients had hyperglycemia of varying severity. Among the risk factors associated with hyperglycemia, age>25 years, family history ofdiabetes and hypertension and BMI >25 have statistically significant association with hyperglycemia. Insulin was started in a total of 40 patients of 47 hyperglycemic patients (85.1%). Mean Insulin dosage required for day 1 was9.66 units. Among the 40 patients started on Insulin 15 (37.5 %) had to be continued on Insulin on Day 7 after steroid administration. Conclusion Significant hyperglycemia can occur in normoglycemic women also leading to serious maternal- fetal consequences . Testing of all antenatal patients especially in age group more than 25years, BMI over 25, hypertensive patients, family history of diabetes who are at risk for development of hyperglycemia ie recommended and start insulin accordingly thus preventing complications.

Irene Giacchetta

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Hongyi Li

and 4 more

The aim of this paper was to compare the prediction performance of three strategies: general global Partial least squares regression (PLSR) using CSSL with and without spiking samples, memory-based learning (MBL) using CSSL with and without spiking samples and general PLSR using only spiking samples to predict soil organic matter in the target area. When using spiked subsets, we also investigated the prediction performance of the extra-weighted subsets. A series of spiking subsets randomly selected from the total spiking samples were selected by conditioned Latin hypercube sampling (cLHS) from the target sites. We calculated the mean squared Euclidean distance (msd) of different spiking subsets with the distribution density function of their vis–NIR spectra only and statistically inferred the optimal sampling set size to be 30. Our study showed that when the number of spiking were lower than 30, the predicted accuracy derived from global PLSR using CSSL spiked with and without extra-weighted samples was greater than the predicted accuracy derived from the general PLSR using the corresponding number of spiking samples only (RMSE 5.57–5.98 v.s. RMSE 6.76). Global PLSR using CSSL spiked with the statistically optimal local samples can achieve higher predicted performance (with a mean RMSE of 5.75). MBL spiked with five extra-weighted optimal spiking samples achieved the best accuracy with an RMSE of 3.98, an R2 of 0.70, a bias of 0.04 and an LCCC of 0.81. The msd is a simple and effective method to determine an adequate spiking size using only vis–NIR data.

Wenzhao Bao

and 3 more

Florian Stehlin

and 11 more

Background: The newly developed mRNA-based COVID-19 vaccines can provoke anaphylaxis, possibly induced by polyethylene glycol (PEG) contained in the vaccine. The management of persons with a history of PEG allergy, or with an allergic-like reaction after the first dose remains to be defined.  Methods: We studied two cohorts of individuals: one pre-vaccination, the second post-vaccination. Skin testing was performed with COVID-19 mRNA vaccines. Upon negative skin test, a two-step (10%-90%) vaccination protocol was performed. Positive skin tests were confirmed with basophil activation tests (BAT). Vaccine-sensitized patients were offered a five-step induction protocol. Results: We identified 187 patients with high-risk profiles for developing anaphylaxis. In parallel, among 385’926 doses of vaccine, 87 allergic-like reactions were reported to our division for further investigations: 18/87 (21%) were consistent with anaphylaxis, 78/87 (90%) were female, and 47/87 (54%) received the BNT162b2 mRNA vaccine. Vaccine skin tests were negative in 96% and 76% in the pre- and post-vaccination cohorts, respectively. A two-step vaccination was tolerated in 232/236 (98%) of individuals with negative tests. Four individuals experienced acute asthma exacerbation during the two-step challenge. Vaccine-positive skin tests were consistently confirmed by BAT; CD63 and CD203c expression was selectively inhibited with ibrutinib, suggesting an IgE-dependent mechanism. Finally, 13 sensitized patients were successfully vaccinated with a five-step vaccination protocol. Conclusion: A two-step 10%-90%-vaccination protocol can be safely administered upon negative skin testing. Yet, it should be delayed in individuals with poorly controlled asthma. Importantly, mRNA vaccine sensitized individuals may receive a five-step vaccination protocol.

Talip E. Eroglu

and 4 more

Aim Depolarization-blocking drugs (DB-drugs) used for cardiac disease increase the risk of cardiac arrhythmia (ventricular tachycardia/ventricular fibrillation[VT/VF]) and out-of-hospital cardiac arrest (OHCA) in specific patient groups. However, it is unknown whether drugs for non-cardiac disease that block cardiac depolarization as off-target effect increase the risk of OHCA on a population level. Therefore, we aimed to investigate OHCA-risk of non-cardiac DB-drugs in the community. Methods We conducted a population-based case-control study. We included OHCA-cases from an Emergency Medical Services attended OHCA-registry in the Netherlands (ARREST:2009-2018), and age/sex/OHCA-date matched non-OHCA-controls. We calculated adjusted odds ratios (ORadj) of use of non-cardiac DB-drugs for OHCA, using conditional logistic regression. Stratified analyses were performed according to first-registered rhythm (VT/VF or non-VT/VF), sex and age (≤50, 50-70, or ≥70 years). Results We included 5,473 OHCA-cases of whom 427 (7.8%) used non-cardiac DB-drugs, and 21,866 non-OHCA-controls of whom 835 (3.8%) used non-cardiac DB-drugs, and found that non-cardiac DB-drug use was associated with increased OHCA-risk when compared to no-use (ORadj1.6[95%-CI:1.4-1.9]). Stratification by first-recorded rhythm revealed that this applied to OHCA with non-VT/VF (asystole) (ORadj2.5[95%-CI:2.1-3.0]), but not with VT/VF (ORadj1.0[95%-CI:0.8-1.2];P-value interaction<0.001). The risk was higher in women (ORadj 1.8[95%-CI:1.5-2.2] than in men (ORadj1.5[95%-CI:1.2-1.8];P-value interaction=0.030) and at younger age (ORadj≥70yrs1.4[95%-CI:1.2-1.7];ORadj50-70yrs1.7[95%-CI:1.4-2.1];ORadj≤50yrs3.2[95%-CI:2.1-5.0];P-value interaction<0.001). Conclusions Use of non-cardiac DB-drugs is associated with increased OHCA-risk in the general population. This increased risk occurred in patients in whom non-VT/VF was the first-registered rhythm, and it occurred in both sexes, but more prominently among women, and more strongly in younger patients (≤50 years).

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Sangjun Yoo

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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 massimo.dipierro@gmail.com

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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