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Background: Heart transplantations are ideal for most patients with end-stage heart failure refractory to medical treatment. The transplantation program at the Peruvian National Heart Institute started with a 10-year-continuity in 2010. Objective: To report the results of a 10-year heart transplantation experience at the Peruvian National Heart Institute. Methods: We studied 83 patients who underwent orthotopic heart transplantation at a single center between January 2010 and December 2019. The recipients’ profiles and survival were analyzed according to sex and age group, ensuring the information’s confidentiality. Results: The recipients’ mean age was 41.2 ± 17 years, 88% were adult, and 68.7% were male. The main indications for transplantation were idiopathic dilated cardiomyopathy. 85.5% of recipients were clinically categorized as INTERMACS Profile 1 to 3 before transplantation. There was a significant difference between sexes regarding the preoperative left ventricular ejection fraction and between age groups regarding the waiting time. The average ischemia time was 3.1 hours, operating time was 6.1 hours, cardiopulmonary bypass time was 3 hours, and aortic cross-clamp time was 1.7 hours. The principal early postoperative complications were hematological disorders and acute kidney failure. The principal late ones were kidney failure and severe anemia. The postoperative mortality was 15.9%, and the principal causes were infection and then acute rejection. The survival at one, five, and ten years was 87.5%, 79.8%, and 79.8%, respectively. The survival results were not influenced by sex or age group. Conclusion: Our patients’ postoperative complications, mortality, and survival rates coincided with those reported by the ISHLT registry.

Meghan Towne

and 7 more

Chunsong Hu

and 2 more

This article introduces briefly current status in managing type 2 diabetes (T2D) and an updated classical standardized comprehensive program which combines optimal medical treatment (OMT) with lifestyle modification, that is, intervention of RT-ABCDEFG (iRT-ABCDEFG) for control and prevention of T2D, and discusses its advantages and prospects. Here, G means goals; F means follow-up; E means examination; D means disease & risk factors control; C means changing unhealthy “environment-sleep-emotion-exercise-diet” intervention [E(e)SEEDi] lifestyle & Chinese medicine or control the source of infection & cutting genetic or spreading pathways during the COVID-19 pandemic; B means biohazard control; And A means antagonistic treatment, such as optimal anti-diabetic agents, the glucagon-like peptide-1 receptor (GLPR) agonists, the sodium-glucose cotransporter 2 (SGLT2) inhibitors, and the ultralong-acting, once-daily basal insulin. As a novel strategy for Intervention of diabetes, this program can be used as a Reverse, Right, and Routine Treatment in clinical practice. Moreover, the vital goals which include less major adverse cardiocerebrovascular events (MACCE) and diabetic complications, less medical costs, longer life expectancy, lower morbidity and mortality, and higher quality of life, will be realized by consistently practicing this program due to early diagnosis, OMT, and overall prevention. Whatever, this program is very helpful to manage or self-manage T2D and improve its outcomes since it highly links to cardiovascular disease (CVD), stroke, cancer, and other MACCEs.

Joeselle Serrana

and 1 more

The development and evaluation of DNA metabarcoding protocols for haplotype-level resolution require attention, specifically for population genetic analysis, i.e., parallel estimation of genetic diversity and dispersal patterns among multiple species present in a bulk sample. Further exploration and assessment of the laboratory and bioinformatics strategies are warranted to unlock the potential of metabarcoding-inferred population genetic analysis. Here, we assessed the inference of freshwater macroinvertebrate haplotypes from DNA metabarcoding data using mock samples with known Sanger-sequenced haplotypes. We also examined the influence of different DNA template concentrations and PCR cycles on detecting true haplotypes and the reduction of spurious haplotypes obtained from DNA metabarcoding. We tested our haplotyping strategy on a mock sample containing 20 specimens from four species with known haplotypes based on the 658-bp Folmer region of the mitochondrial cytochrome c oxidase gene. The read processing and denoising step resulted in 14 zero-radius operational taxonomic units (ZOTUs) of 421-bp length, with 12 ZOTUs having 100% match with 12 of the Sanger haplotype sequences. Quality passing reads relatively increased with increasing PCR cycles, and the relative abundance of each ZOTUs was consistent for each cycle number. This suggests that increasing the cycle number from 24 to 64 did not affect the relative abundance of quality passing filter reads of each ZOTUs. Our study demonstrated the ability of DNA metabarcoding to infer intraspecific variability while highlighting the challenges that need to be addressed before its possible applications to population genetic studies.

Xujin Yao

and 13 more

Background and Purpose: Isoleucine is a branched-chain amino acid serving as an essential nutrient resource and metabolic. However, its role in cerebral ischemic stroke remains unknown. Experimental Approach: Middle cerebral artery occlusion (MCAO) was used to mimic in vivo model of stroke. Oxygen-glucose deprivation insult (OGD) was used to injure cultured cortical neurons. High-Performance Liquid Chromatography (HPLC) was used to measure the level of isoleucine. A western blot assay and immunofluorescent staining were used to measure the level of CBFB and PTEN. TTC staining was used to measure the infarct size. Cell death and viability were assessed by LDH and CCK8 assays. DCS was used to stimulate cortical neurons. tDCS was used to stimulate the cortex. Key Results: Extraneuronal isoleucine is decreased and intraneuronal isoleucine is increased after rat cerebral I/R injury. Reducing intraneuronal isoleucine via inhibition of its transporter, LAT1 promotes neuronal survival whereas supplementing isoleucine aggravates neuronal damage. Isoleucine downregulates the expression of CBFB, and that acts upstream of PTEN to mediate isoleucine-induced neuronal damage after OGD insult. To identify the therapeutic approach that suppresses the ischemia-induced increase of intraneuronal isoleucine, we tested the effect of tDCS on isoleucine. Our data suggest that Cathodal tDCS can reduce cerebral infarct size. And such neuroprotection is mediated through reducing LAT1-dependent increase of intraneuronal isoleucine. Conclusions and Implications: This study identifies LAT1- dependent increase of intraneuronal isoleucine promotes neuronal death after rat cerebral I/R injury. Our results indicate that tDCS protects against rat cerebral I/R injury through regulating LAT1-isoleucine-CBFB-PTEN signaling.

Shouning Zhou

and 6 more

Aim: To establish a population pharmacokinetic model and optimise tacrolimus dosing regimens in Chinese Han lung transplant recipients. Methods: Tacrolimus trough concentrations and clinical data of 70 adult lung transplant recipients were collected. Population pharmacokinetic analysis was performed using a nonlinear mixed effects model. A Monte Carlo simulation was conducted to determine the optimal dosing regimen. Results: The pharmacokinetics of tacrolimus could be best described by a one-compartment model, with the CYP3A5 genotype, haematocrit (HCT), and alanine transaminase (ALT) as significant covariates. The clearance of tacrolimus in the CYP3A5 rapid and intermediate metabolisers were 3.03 and 1.99 times higher than those of CYP3A5 poor metaboliser, respectively. When HCT decreased from 0.30 to 0.20, the clearance of tacrolimus increased by 31.14%, and the apparent volume of distribution increased by 28.58%. The clearance of tacrolimus decreased by 8.67% when ALT increased from 20 IU·L-1 to 40 IU·L-1. Monte Carlo simulation indicated that recipients with CYP3A5*1/*1 receiving 3.5 mg twice daily, recipients with HCT < 0.2 receiving 5 mg twice daily, and recipients with ALT < 4IU·L-1 received 3 mg twice daily, could achieve the target concentrations of 10–15 ng·mL-1. Conclusions: A population pharmacokinetic model of tacrolimus in Chinese Han lung transplant recipients was successfully constructed. Recipients with the CYP3A5*1/*1 genotype, low HCT value, and low ALT value after surgery needed a higher maintenance dose to reach the therapeutic window, which provided a reference for the formulation of individualised tacrolimus regimen.

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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

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