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Doaa Emam

and 11 more

Objective To document longitudinal changes in brain development in fetuses with congenital diaphragmatic hernia (CDH). Design Retrospective cohort study Setting Single tertiary fetal surgery center Population Fetuses with isolated CDH and at least two MRI-examinations (n=42 fetuses). Fifty-six fetuses who underwent MRI for a condition not interfering with fetal brain development or fetuses from healthy volunteers served as controls. Methods Biometry included biparietal and fronto-occipital diameter, ventricular atrial width, transcerebellar diameter, head circumference and width of the extra-axial space. Cortical maturation was assessed using a qualitative and quantitative grading system. 3D volumes were segmented for white matter, intra-axial and extra-axial cerebrospinal fluid and cerebellum. Main outcome measures Brain development on MRI with subjective and objective assessment. Results The mean GA at first MRI was 28.0 ± 2.1 wks and at the second 33.2 ± 1.3 wks. The mean GA in controls was 30.7 ± 4.2 wks. At 28 weeks CDH fetuses displayed abnormal maturation grading (p<0.003) and fissure depth (p<0.05). By 33 wks, the brain grading indices were still abnormal (p<0.01), but fissure depth measurements were in the normal range (p>0.05). Also, the extra-axial fluid and the ventricular volume were increased (resp. p 0.0054 and p 0.0243). There was no difference in white matter or cerebellum volume (p>0.05). Conclusions Brain development in CDH fetuses around 28 weeks appears to be delayed. This is less prominent at 33 weeks. In addition, there was an increase in ventricular and extra-axial space volume in the third trimester.

Cian Tan

and 1 more

Background Since the introduction of the E-Vita Open NEO aortic prosthesis in 2020, several incidences of post-anastomotic oozing from the polyester portion of the graft have emerged. The use of BioGlue to prime E-Vita Open NEO to prevent this has been suggested as a way to mitigate this worrying complication. We investigate the extent of graft oozing in E-Vita Open NEO and evaluate the use of BioGlue in preventing oozing, both experimentally and in terms of potential clinical complications. Methods and materials E-Vita Open NEO (in straight and branched configurations) was implanted in a perfused model. The distal stent-graft and side branches were clamped, and the graft pressurised with blood to 120 mmHg. The volume of blood (ml) oozing from the graft within 60 seconds was measured. Non-pressurised grafts were coated with BioGlue up to a thickness 1-, 2-, and 3 mm, and the volume (mm3) of BioGlue required to do so was recorded. Results Within 60 seconds, 250.0 ml of blood oozed from the grafts tested. 43.694 mm3, 87.389 mm3, and 174.778 mm3 of BioGlue was required to coat the device with 1-, 2-, and 3 mm of BioGlue. Conclusion Graft oozing from E-Vita Open NEO represents an omnipresent and worrying risk. The use of BioGlue herein is likely associated with several adverse consequences, which are an additional risk on top of that posed by graft oozing. These risks call into question the suitability of E-Vita Open NEO, especially when compared to alternative devices not affected by oozing.

Hao Pu

and 1 more

Toshiaki Jo

and 1 more

Environmental DNA (eDNA) analysis is a promising tool for non-disruptive and cost-efficient estimation of species abundance. However, its practical applicability in natural environments is limited because it is unclear whether eDNA concentrations actually represent species abundance in the field. Although the importance of accounting for eDNA dynamics, such as transport and degradation, has been discussed, the influences of eDNA characteristics, including production source and state, and methodology, including collection and quantification strategy and abundance metrics, on the accuracy of eDNA-based abundance estimation were entirely overlooked. We conducted a meta-analysis using 56 previous eDNA literature and investigated the relationships between the accuracy (R2) of eDNA-based abundance estimation and eDNA characteristics and methodology. Our meta-regression analysis found that R2 values were significantly lower for crustaceans than fish, suggesting that less frequent eDNA production owing to their external morphology and physiology may impede accurate estimation of their abundance via eDNA. Moreover, R2 values were positively associated with filter pore size, indicating that selective collection of larger-sized eDNA, which is typically fresher, could improve the estimation accuracy of species abundance. Furthermore, R2 values were significantly lower for natural than laboratory conditions, while there was no difference in the estimation accuracy among natural environments. Our findings shed a new light on the importance of what characteristics of eDNA should be targeted for more accurate estimation of species abundance. Further empirical studies are required to validate our findings and fully elucidate the relationship between eDNA characteristics and eDNA-based abundance estimation.

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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.

Laura Küpfer

and 6 more

Background. The treatment of childhood acute lymphoblastic leukemia (ALL) remains challenging in low-income countries. Here we evaluate the experience with a modified Berlin-Frankfurt-Münster (BFM) treatment protocol ALL-Moscow Berlin (MB)-91 at the Kantha Bopha hospitals, a charity-funded institution providing free pediatric care in Cambodia. Methods. This is a retrospective study including 110 unselected patients aged 9 months to 14 years diagnosed with ALL between 2015 and 2017. Patients were stratified in high- (HR) and standard-risk (SR) groups based on clinical criteria. The cumulative doses of anthracyclines were reduced to 120 mg/m2 for SR patients and consolidation was based on Capizzi methotrexate elements instead of cyclophosphamide, cytarabine and high dose methotrexate. Supportive empiric antibiotic treatment and whole blood transfusions were possible. Results. 63 patients (57 %) were HR, mostly based on high leukemia burden with hyperleukocytosis > 50 G/l, massive lymph node and hepato-splenic involvement, reflecting a high disease burden. 72 patients (65.5%) reached complete remission (CR) on day 36. The estimated 3-year overall survival (OS) was 34.9 %, 50.5 % for SR and 23.4 % for HR patients. Most events were due to severe infections (40 (53.3 %)) and bleeding (15 (20 %)), mostly during induction and consolidation. Relapse was confirmed in 13 cases (11.8 %). No patients abandoned treatment. Conclusion. ALL chemotherapy is feasible in a charity-funded public institution with results comparable to other low-middle income countries, but treatment-related mortality remains limiting. This will justify investments in diagnostics to stratify more patients for reduced intensity treatment and in supportive care.

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

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