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IL-36 has been implicated in the pathogenesis of spondyloarthropathies (SpA) like psoriasis and inflammatory bowel disease. Enthesitis related arthritis (ERA) category of juvenile idiopathic arthritis is a form of juvenile SpA, however no data is available on the role of IL-36 in this disease. IL-36α, β, γ and IL-36R mRNA expression in blood and synovial fluid mononuclear cells and IL-36α, γ, IL-36Ra, IL-6 and IL-17 levels were measured in serum and synovial fluid (SF). IL-36γ production by fibroblast like synoviocytes (FLS) by pro-inflammatory cytokines and its effect on FLS was also studied.mRNA levels of IL-36α, IL-36γ and IL-36R were increased in PBMCs of ERA patients as compared to healthy controls however only IL-36γ was measurable in serum of one third of patients. In SFMCs, all 4 mRNA were detectable but were lower than RA patients. SF IL-36γ levels correlated with disease activity score (r=0.51, p< 0.0001), SF IL-6 (r=0.4,p= 0.0063) and IL-17 levels (r=0.57,p=0.0018). Pro-inflammatory cytokines increased expression of IL-36γ and IL-6 in FLS cultures. SFs from 5 ERA patients also increased expressions of IL-36γ and IL-6 in FLS which could be blocked by using IL-36Ra.This suggests that pro-inflammatory cytokines aid in upregulation of IL-36γ which in turn upregulates expression of IL-6. This might lead to a positive feedback loop of inflammation in ERA. Association of SF levels of IL-36γ with disease activity further supports this possibility. IL-36Ra based therapy may have a role in ERA.
We previously showed increased steroid resistant CD28null CD8+ senescent lymphocyte subsets in peripheral blood from COPD patients. These cells expressed decreased levels of the glucocorticoid receptor (GCR), suggesting their contribution to the steroid resistant property of these cells. COPD is a disease of the small airways. We therefore hypothesized that there would be a further increase in these steroid resistant lymphocytes in the lung, particularly in the small airways. We further hypothesized that the pro-inflammatory/cytotoxic potential of these cells could be negated using prednisolone with low-dose cyclosporin A.Blood, bronchoalveolar lavage, large proximal and small distal airway brushings were collected from 11 COPD patients and 10 healthy aged-matched controls. The cytotoxic mediator granzyme b, pro-inflammatory cytokines IFNγ/TNFα, and GCR were determined in lymphocytes subsets before and after their exposure to 1µM prednisolone and/or 2.5ng/mL cyclosporin A.Particularly in the small airways, COPD subjects showed an increased percentage of CD28null CD8 T-cells and NKT-like cells, with increased expression of granzyme b, IFNγ and TNFα and a loss of GCR, compared with controls. Significant negative correlations between small airway GCR expression and IFNγ/TNFα production by T and NKT-like cells (eg, T-cell IFNγ R= -.834, p=.031) and with FEV1 (R= -890) were shown. Cyclosporine A and prednisolone synergistically increased GCR expression and inhibited pro-inflammatory cytokine production by CD28null CD8- T and NKT-like cells.COPD is associated with increased pro-inflammatory CD28null CD8+ T and NKT-like cells in the small airways. Treatments that increase GCR in these lymphocyte subsets may improve morbidity in COPD patients.

Elena Berenice Martínez-Shio, Ángel Martín Cárdenas-Hernández, Verónica Jiménez-Suárez, Laura Sherell Marín-Jáuregui, Claudia Castillo-Martin del Campo, Roberto González-Amaro, Carlos D Escobedo-Uribe

and 1 more

IntroductionDyslipidemia is one of the main modifiable risk factors for the development of cardiovascular diseases (CVD), being the ischemic heart disease the leading cause of mortality in the world. Every year, more people die from CVD than from any other reason, according to data from the World Health Organization, it is estimated that 17.9 million people died from this cause in 2019, which represents 32% of all registered deaths in the world . In addition to high blood pressure, diabetes, obesity, and smoking, dyslipidemia is one of the main cardiovascular risk factors. The latter it is defined as disorders in blood lipids characterized by an increase in cholesterol and/or triglyceride levels called hypercholesterolemia and triglyceridemia, respectively .While most of the triglyceride and cholesterol content is obtained from dietary sources, de novo lipogenesis contributes significantly to serum lipid content in people who have a high-carbohydrate diet. The metabolic pathways by which the macromolecules obtained through the diet are processed, such as glycolysis, Krebs cycle, oxidative phosphorylation, beta oxidation, among others, have as their main function the generation of energy, and an imbalance in these can promote pathological processes, such as dyslipidemia . These metabolic pathways not only provide energy for cellular homeostasis, but also control immune cell functions. Immune cells at rest, use processes such as Krebs cycle and oxidative phosphorylation for ATP generation, but cells with pro-inflammatory phenotype such as M1 macrophages and activated T lymphocytes tend to change to aerobic glycolysis, while M2 macrophages and regulatory T lymphocytes induced in the periphery continue with oxidative phosphorylation. Reprogramming of the metabolic state of immune cells influences the generation of epigenetic changes which lead to functional changes. This cellular metabolic state is affected by systemic metabolism, either by nutrients availability or by signalling pathways induced by each metabolite . These concepts are the basis of innate immunological memory, this phenomenon, also called immune training, is defined by metabolic changes originated after priming with pathogens or sterile stimuli that lead to sustained functional changes orchestrated mainly by epigenetic reprogramming, which are sustained changes in gene expression and cellular physiology, which does not imply permanent changes .An immune cell type that attracts more attention in the immunometabolism area is the macrophages population. Macrophages are phagocytic cells of innate immunity with a broad functional spectrum, from pro-inflammatory to anti-inflammatory phenotypes representing the extremes. Monocytes, cells that develop from bone marrow precursors, travel in bloodstream for a few days, then they migrate to tissue and become macrophages with different phenotypes . Tissue-resident macrophages are long-lived cells derived mostly from erythro-myeloid progenitors that emerge from the yolk sac . The first to emerge are the primitive macrophages, which are not derived from monocytes and seed every tissue. When erythro-myeloid progenitors seed the fetal liver, they generate fetal monocytes that differentiate into macrophages, and represent the most abundant tissue-resident macrophage population . Furthermore, monocytes derived from hematopoietic stem cells emerge from the fetal liver and differentiate into long-lived macrophages, while adult hematopoiesis begins in the bone marrow. Bone marrow -derived monocytes contribute to the different populations of postnatal tissue resident macrophages .Monocytes/ macrophages are recognized because their important roles in regulating homeostasis and immune defense through their inflammatory or tissue repair properties . The importance of metabolism in immune cells for the programming of macrophages with their different functional spectra suggests that metabolic pathways may play a role for long-term functional changes in monocytes and macrophages during immune training . The role of these cells is widely described in obesity, being the main population present in the adipose tissue stromal vascular fraction, where there is an increase in the proliferation of macrophages coupled with the recruitment of circulating monocytes to this tissue. Due to the production of cytokines such as IL-1β, IL-6 and TNF-α, M1 macrophages participate in the low-grade chronic inflammation that characterizes obesity .In past years, it has been shown that when treating monocyte derived macrophages with high concentrations of insulin, glucose and palmitate, characteristic of metabolic syndrome, a different pro-inflammatory phenotype is induced. These cells present surface markers and transcription factors different from classical macrophages and were called metabolically activated macrophages (MMe) . MMe present surface molecules such as CD36, which binds to long chain fatty acids and facilitates their transport in the cell, participating in the use of lipids in muscle, storage of adipose energy and absorption of intestinal fat ; ABCA1 is a cholesterol efflux pump in the elimination pathway of cellular lipids that are then collected by apoA-I, forming high-density lipoproteins (HDL) ; and PLIN2, which is a protein expressed on the lipid droplet membrane . These MMe have been described in metabolic syndrome and have been found in adipose tissue during obesity, performing beneficial and detrimental functions during diet-induced obesity in mice , and in mammary adipose tissue promoting tumorigenesis during obesity . MMe produce pro-inflammatory cytokines, although in a lesser extent than classic M1 macrophages. The expression of their characteristic surface markers, as well as the attenuated inflammatory response, is mainly mediated by the transcription factor PPAR-γ , that could be contributing to the chronic low-grade inflammatory state present in metabolic syndrome and obesity.Due to dietary overload, the metabolites produced by the different metabolic pathways can be used for alternative pathways in organs and tissues, such as adipose tissue, modifying and defining systemic metabolic responses It is not completely clear whether the change from a healthy systemic metabolic state to a pathological one, such as the dyslipidemic state, lead to changes causing immune training influencing polarization to different cell types.The aim of this study was to evaluate if high cholesterol and triglycerides levels, main feature of dyslipidemia, are promoting immune training in peripheral blood cells, functioning as a first stimulus, conditioning monocytes to present a metabolic phenotype and leading them to polarization into metabolically activated macrophages. We found that monocytes with metabolic phenotype expressing CD36, ABCA1 and PLIN2, are present in systemic circulation. In vitro stimulation showed that MMe from patients with dyslipidemia, play a dynamic role with production of pro- and anti-inflammatory cytokines.
IntroductionKawasaki disease (KD) , also known as Kawasaki syndrome, is an acute, self-limited febrile vasculitis that predominantly affects infants and children under 5 years of age [1]. KD is characterized by high spiking fever persisting for more than 5 days, erythematous rash, bilateral conjunctivitis, congestive oral mucosa, swelling lymph node, and edematous extremity [2]. Furthermore, KD is the most common cause of acquired cardiac disease, especially coronary artery aneurysms in children [3]. Although KD has been studied for almost half a century, the pathogenic mechanism of KD remains unclear. Furthermore, while most patients respond well to intravenous immunoglobulin (IVIG), roughly one-quarter of the children meeting clinical criteria will go on to have coronary artery inflammation, including aneurysms [4]. Hence, further illustration of the mechanism of KD is a crying need to find a therapeutic for KD treatment clinically.Both innate and adaptive immune systems are involved in the pathogenesis of KD [5]. The early event of visualized immunological abnormality is the activation of innate immune system represented as the elevated numbers of activated monocytes and increased expression of circulating cytokines, such as interleukin (IL)-6 and tumor necrosis factor (TNF) -α [6]. Subsequently, it is generally believed that autoreactive T cell and their inflammatory cytokines play a major role in the development of KD [7]. T helper (Th) 17 cells, a recently identified lineage of CD4+ Th cells, predominantly produce IL-17A. Th17 cell and IL-17A have been shown to participate in host defense responses and inflammatory diseases, such as systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), Graves’ disease (GD), and Crohn’s disease (CD) [8-11]. A recent study has shown that a high frequency of Th17 cells and high levels of IL-17 were demonstrated in the acute stage of KD, and that elevated Th17 cells might be associated with tissue damage and coronary artery aneurysm formation [7, 12]. However, there is little information about whether higher frequency of Th17 and higher concentrations of IL-17A also exist in Chinese patients with KD and how Th17 responses are associated with the development of coronary artery aneurysm in KD patients.More notably, a newly identified T-cell subset, termed Th22 cells, has been described as expressing their key cytokines interleukin (IL)-22, which can activate signal transduction and transcription 3 (STAT3) [13]. IL-22, originally termed as an IL-10-related T-cell-derived-inducible factor, enhance innate immunity and promote epithelial cell proliferation and tissue. In contrast, IL-22 also act as regulator in the pathogenesis of RA and SLE [14-15]. Furthermore, recent studies have reported that IL-22 may function as a biphasic cytokine: protective and regenerative in steady state while amplifying proinflammatory signals given by TNF-α [16], which is necessary for exacerbation of vascular injury in KD. However, little is known about the role of Th22 cells in the pathogenesis of KD. We believe that Th22 cells may partially contribute to the formation of coronary aneurysms.Here, in the current study, we sought to further clarify the mechanism underlying hyperactivation of Th22 and Th17 during acute KD. We characterized the numbers of circulating Th22 and Th17 cells by flow cytometry, and measured the concentration of serum inflammatory cytokines by enzymelinked immunosorbent assay (ELISA) in 43 Chinese patients with new onset KD. Furthermore, we analyzed the potential association of the numbers of Th22 and Th17 cells with the clinical measures in these KD patients. Our findings indicated that increased numbers of Th22 and Th17 cells might be contributed to the pathogenesis of KD in Chinese patients.

Tianhong Xie

and 1 more

To date, the mechanism of systemic lupus erythematosus (SLE) has not been thoroughly deciphered. Recent research demonstrated that CD138+ T cells accumulate in an SLE murine model, indicating that they are autoreactive T cells that significantly promote autoantibody production. Double negative (DN) T cells have been demonstrated to participate in the progression of SLE, but their detailed mechanism and the role in SLE remain unclear. Importantly, the expression of CD138 in CD3+ T cells plays a key role in the progression of lupus; it causes the accumulation of autoreactive T cells, including DN T cells, by significantly preventing their apoptosis. T helper 1 cells and interferon gamma both prevail in SLE; they may play essential roles in building the inflammatory condition of SLE. Defects occur in regulatory B (Breg) cells during their expansion in SLE, resulting in more differentiation of activated B cells into plasma cells; this subsequently increases antibody production. Myeloid-derived suppressor cells (MDSCs) enhance the expansion of Breg cells. However, the sustained increase of cytokine levels in SLE promotes the differentiation of more MDSCs into macrophage and dendritic cells, resulting in the defective expansion of MDSCs. The defective expansion of Breg cells and MDSCs breaks the immune-tolerance milieu in SLE, resulting in increased autoantibody secretion from those abnormal plasma cells. This review discusses recent advances regarding the detailed roles and mechanisms of these immunocytes in SLE.
ACE-2 receptor plays a vital role not only in the SARS-CoV-induced epidemic but also in some diseases. Studies have been carried out on the interactions of ACE-2- SARS-CoV proteins. However, comprehensive research has not been conducted on ACE2 protein by using bioinformatic tools. The present study especially two places, G104 and L108 points, which are effective in protecting the structure of the ACE-2 protein, play a critical role in the biological functioning of this protein, and play an essential role in determining the chemical-physical properties of this protein, and play a crucial role for ACE-2 protein-SARS CoV surface glycoprotein, were determined. It was also found that the G104 and L108 regions were more prone to possible mutations or deletions than the other ACE-2 protein regions. Moreover, it was determined that all possible mutations or deletions in these regions affect the chemical-physical properties, biological functions, and structure of the ACE-2 protein. Having a negative GRAVY value, one transmembrane helix, a significant molecular weight, a long-estimated half-life as well as most having unstable are results of G104 and L108 points mutations or deletions. Finally, it was determined that LQQNGSSVLS, which belong to the ACE-2 protein, may play an active role in binding the spike protein of SARS-CoV. All possible docking score results were estimated. It is thought that this study will bring a different perspective to ACE-2 _SARS-CoV interaction and other diseases in which ACE-2 plays an important role and will also be an essential resource for studies on ACE-2 protein.

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Colum Keohane

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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.

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

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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.
Many high-performance computing applications are of high consequence to society. Global climate modeling is a historic example of this. In 2020, the societal issue of greatest concern, the still-raging COVID-19 pandemic, saw a legion of computational scientists turning their endeavors to new research projects in this direction. Applications of such high consequence highlight the need for building trustworthy computational models. Emphasizing transparency and reproducibility has helped us build more trust in computational findings. In the context of supercomputing, however, we may ask: how do we trust results from computations that cannot be repeated? Access to supercomputers is limited, computing allocations are finite (and competitive), and machines are decommissioned after a few years. In this context, we might ask how reproducibility can be ensured, certified even, without exercising the original digital artifacts used to obtain new scientific results. This is often the situation in HPC. It is compounded now with greater adoption of machine learning techniques, which can be opaque. The ACM in 2017 issued a Statement on Algorithmic Transparency and Accountability, targeting algorithmic decision-making using data models \cite{council2017}. Among its seven principles, it calls for data provenance, auditability, validation and testing. These principles can be applied not only to data models, but to HPC in general. I want to discuss the next steps for reproducibility: how we may adapt our practice to achieve what I call unimpeachable provenance, and full auditability and accountability of scientific evidence produced via computation.An invited talk at SC20I was invited to speak at SC20 about my work and insights on transparency and reproducibility in the context of HPC. The session's theme was Responsible Application of HPC, and the title of my talk was "Trustworthy computational evidence through transparency and reproducibility." At the previous SC, I had the distinction to serve as Reproducibility Chair, leading an expansion of the initiative, which was placed under the Technical Program that year. We moved to make Artifact Description appendices required for all SC papers, created a template and an author kit for the preparation of the appendices, and introduced three new Technical Program tracks in support of the initiative. These are: the Artifact Description & Evaluation Appendices track—with an innovative double-open constructive review process—, the Reproducibility Challenge track, and the Journal Special Issue track, for managing the publication of select papers on the reproducibility benchmarks of the Student Cluster Competition. This year, the initiative was augmented to address issues of transparency, in addition to reproducibility, and a community sentiment study was launched to assess the impact of the effort, six-years in, and canvas the community's outlook on various aspects of it.Allow me to thank here Mike Heroux, Reproducibility Chair for SC in 2017 and 2018, Michela Taufer, SC19 General Chair—who put her trust in me to inherit the role from Mike—, and Beth Plale, the SC20 Transparency and Reproducibility Chair. I had countless inspiring and supportive conversations with Mike and Michela about the topic during the many months of planning for SC19, and more productive conversations with Beth during the transition to her leadership. Mike, Michela and I have served on other committees and working groups together, in particular, the group that met in July 2017 at the National Science Foundation (convened by Almadena Chtchelkanova) for the Workshop on Reproducibility Taxonomies for Computing and Computational Science. My presentation at that event condensed an inventory of uses of various terms like reproducibility and replication, across many fields of science \cite{barba2017}. I then wrote the review article "Terminologies for Reproducible Research," and posted it on arXiv \cite{barba2018}. It informed our workshop's report, which came out a few months later as a Sandia technical report \cite{taufer2018}. In it, we highlighted that the fields of computational and computing sciences provided two opposing definitions of the terms reproducible and replicable, representing an obstacle to progress in this sphere.The Association of Computing Machinery (ACM), representing computer science and industry professionals, had recently established a reproducibility initiative, and adopted diametrically opposite definitions to those used in computational sciences for more than two decades. In addition to raising awareness about the contradiction, we proposed a path to a compatible taxonomy. Compatibility is needed here because the computational sciences—astronomy, physics, epidemiology, biochemistry and others that use computing as a tool for discovery—and computing sciences (where algorithms, systems, software, and computers are the focus of study) have community overlap and often intersect in the venues of publication. The SC conference series is one example. Given the historical precedence and wider adoption of the definitions of reproducibility and replicability used in computational sciences, our Sandia report recommended that the ACM definitions be reversed. Several ACM-affiliated conferences were already using the artifact review and badging system (approved in 2016), so this was no modest suggestion. The report, however, was successful in raising awareness of the incompatible definitions, and the desirability of addressing it.A direct outcome of the Sandia report was a proposal to the National Information Standards Organization (NISO) for a Recommended Practice Toward a Compatible Taxonomy, Definitions, and Recognition Badging Scheme for Reproducibility in the Computational and Computing Sciences. NISO is accredited by the American National Standards Institute (ANSI) to develop, maintain, and publish consensus-based standards for information management. The organization has more than 70 members; publishers, information aggregators, libraries and other content providers use its standards. I co-chaired this particular working group, with Gerry Grenier from IEEE and Wayne Graves from ACM; Mike Heroux was also a member. The goal of the NISO Reproducibility Badging and Definitions Working group was to develop a Recommended Practice document—a step before development of a standard. As part of our joint work, we prepared a letter addressed to the ACM Publications Board, delivered in July 2019. It described the context and need for compatible reproducibility definitions and made the concrete request that ACM consider a change. By that time, not only did we have the Sandia report as justification, but the National Academies of Sciences, Engineering and Medicine (NASEM) had just released the report Reproducibility and Replicability in Science \cite{medicine2019}. It was the product of a long consensus study conducted by 15 experts, including myself, and sponsored by the National Science Foundation responding to Congressional decree. The NASEM report put forth its definitions as:Reproducibility is obtaining consistent results using the same input data, computational steps, methods and code, and conditions of analysis.Replicability is obtaining consistent results across studies aimed at answering the same scientific question, each of which has obtained its own data.The key contradiction with the ACM badging system resides on which term comprises using the author-created digital artifacts (e.g., data and code). We stated in the NISO working-group letter that if the ACM definitions of reproducible and replicable could be interchanged, the working group could move forward towards its goal of drafting recommended practices for badging that would lead to wider adoption in other technical societies and publishers. The ACM Publications Board responded positively, and began working through the details on how to make changes to items already published in the Digital Library with the "Results Replicated" badge—about 188 items existed at that time that were affected. Over the Summer of 2020, the ACM applied changes to the published Artifact Review and Badging web pages, and added a version number. From version 1.0, we see a note added that, as a result of discussions with NISO, the ACM was harmonizing its terminologies with those used in the broader scientific research community.All this background serves to draw our attention to the prolonged, thoughtful, and sometimes arduous efforts that have been directed at charting paths for adoption and giving structure to reproducibility and replicability in our research communities. Let us move now to why and how might the HPC community move forward.Insights on transparent, reproducible HPC researchDeployed barely over a year ago, the NSF-funded Frontera system at the Texas Advanced Computing Center (TACC) came in as the 8th most powerful supercomputer in the world, and the fastest on a university campus. Up to 80% of the available time on the system is allocated through the NSF Petascale Computing Resource Allocation program. The latest round of Frontera allocations (as of this writing) was just announced on October 25, 2020. I read through the fact sheet on the 15 newly announced allocations, to get a sense for the types of projects in this portfolio. Four projects are machine-learning or AI-focused, the same number as those in astronomy and astrophysics, and one more than those in weather or climate modeling. Other projects are single instances spanning volcanology/mantle mechanics, molecular dynamics simulations of ion channels, quantum physics in materials science, and one engineering project in fluid-structure interactions. One could gather these HPC projects in four groups:Astronomy and astrophysics are mature fields that in general have high community expectations of openness and reproducibility. As I'll highlight below, however, even these communities with mature practices benefit from checks of reproducibility that uncover areas of improvement. The projects tackling weather and climate modeling are candidates for being considered of high consequence to society. One example from the Frontera allocations concerns the interaction of aerosols caused by industrial activity with clouds, which can end up composed of smaller droplets, and become more reflective, resulting in a cooling effect on climate. Global climate models tend to overestimate the radiative forcing, potentially underestimating global warming: why? This is a question of great consequence for science-informed policy, in a subject that is already under elevated scrutiny from the public. Another project in this cluster deals with real-time high-resolution ensemble forecasts of high-impact winter weather events. I submit that high standards of transparency, meticulous provenance capture, and investments of time and effort in reproducibility and quality assurance are justified in these projects. Four of the winning projects are applying techniques from machine learning to various areas of science. In one case, the researchers seek to bridge the gap in the trade-off between accuracy of prediction and model interpretability, to make ML more applicable in clinical and public health settings. This is clearly also an application of high consequence, but in addition all the projects in this subset face the particular transparency challenges of ML techniques, requiring new approaches to provenance capture and transparent reporting. The rest of the projects are classic high-performance computational science applications, such as materials science, geophysics, and fluid mechanics. Reproducible-research practices vary broadly in these settings, but I feel confident saying that all or nearly all those efforts would benefit from prospective data management, better software engineering, and more automated workflows. And their communities would grow stronger with more open sharing. The question I have is: how could the merit review of these projects nudge researchers towards greater transparency and reproducibility? Maybe that is a question for later, and a question to start with is how could support teams at cyberinfrastructure facilities work with researchers to facilitate their adoption of better practices in this vein? I'll revisit these questions later.I also looked at the 2019 Blue Waters Annual Report, released on September 15, 2020, with highlights from a multitude of research projects that benefitted from computing allocations on the system. Blue Waters went into full service in 2013 and has provided over 35 billion core-hour equivalents to researchers across the nation. The highlighted research projects fall into seven disciplinary categories, and include 32 projects in space science, 20 in geoscience, 45 in physics and engineering, and many more. I want to highlight just one out of the many dozens of projects featured in the Blue Waters Annual Report, for the following reason. I did a word search on the PDF with Zenodo, and that project was the only one listing Zenodo entries in the "Publications & Data Sets" section that ends each project feature. One other project (in the domain of astrophysics) mentions that data is available through the project website and in Zenodo, but doesn't list any data sets in the report. Zenodo is an open-access repository funded by the European Union's Framework Programs for Research, and operated by CERN. Some of the world’s top experts in running large-scale research data infrastructure are at CERN, and Zenodo is hosted on top of infrastructure built in service of what is the largest high-energy physics laboratory of the world. Zenodo hosts any kind of data, under any license type (including closed-access). It has become one of the most used archives for open sharing of research objects, including software.The project I want to highlight is "Molten-salt reactors and their fuel cycles," led by Prof. Kathryn Huff at UIUC. I've known Katy since 2014, and she and I share many perspectives on computational science, including a strong commitment to open-source software. This project deals with modeling and simulation of nuclear reactors and fuel cycles, combining multiple physics and multiple scales, with the goal of improving design of nuclear reactors in terms of performance and safety. As part of the research enabled by Blue Waters, the team developed two software packages: Moltres, described as a first-of-its-kind finite-element code for simulating the transient neutronics and thermal hydraulics in a liquid-fueled molten-salt reactor design; and SaltProc: a Python tool for fuel salt reprocessing simulation. The references listed in the project highlight include research articles in the Annals of Nuclear Energy, as well as the Zenodo deposits for both codes, and a publication about Moltres in the Journal of Open Source Software, JOSS. (As one of the founding editors of JOSS, I'm very pleased.) It is possible, of course, that other projects of the Blue Waters portfolio have also made software archives in Zenodo or published their software in JOSS, but they did not mention it in this report and did not cite the artifacts. Clearly, the research context of the project I highlighted is of high consequence: nuclear reactor design. The practices of this research group show a high standard of transparency that should be the norm in such fields. Beyond transparency, the publication of the software in JOSS ensures that it was subject to peer review and that it satisfies standards of quality. JOSS reviewers install the software, run tests, and comment on usability and documentation, leading to quality improvements.Next, I want to highlight the work of a group that includes CiSE editors Michela Taufer and Ewa Deelman, posted last month on arXiv \cite{e2020}[6]. The work sought to directly reproduce the analysis that led to the 2016 discovery of gravitational waves, using the data and codes that the LIGO collaboration had made available to the scientific community. The data had previously been re-analyzed by independent teams using different codes, leading to replication of the findings, but no attempt had yet been made at reproducing the original results. In this paper, the authors report on challenges they faced during the reproduction effort, even with availability of data and code supplementing the original publication. A first challenge was the lack of a single public repository with all the information needed to reproduce the result. The team had the cooperation of one of the original LIGO team members, who had access to unpublished notes that ended up being necessary in the process of iteratively filling in the gaps of missing public information. Other highlights of the reproduction exercise include: the original publication did not document the precise version of the code used in the analysis; the script used to make the final figure was not released publicly (but one co-author gave access to it privately); the original documented workflow queried proprietary servers to access data, which needed to be modified to run with the public data instead. In the end, the result—the statistical significance of the gravitational-wave detection from a black-hole merger—was reproduced, but not independently of the original team, as one researcher is co-author in both publications. The message here is that even a field that is mature in its standards of transparency and reproducibility needs checks to ensure that these practices are sufficient or can be improved.Science policy trendsThe National Academies study on Reproducibility and Replicability in Science was commissioned by the National Science Foundation under Congressional mandate, with the charge coming from the Chair of the Science, Space, and Technology Committee. NASEM reports and convening activities have a range of impacts on policy and practice, and often guide the direction of federal programs. NSF is in the process of developing its agency response to the report, and we can certainly expect to hear more in the future about requirements and guidance for researchers seeking funding.The recommendations in the NASEM report are directed at all the various stakeholders: researchers, journals and conferences, professional societies, academic institutions and national laboratories, and funding agencies. Recommendation 6-9, in particular, prompts funders to ask that grant applications discuss how they will assess and report uncertainties, and how the proposed work will address reproducibility and/or replicability issues. It also recommends that funders incorporate reproducibility and replicability in the merit-review criteria of grant proposals. Combined with related trends urging for more transparency and public access to the fruits of government-funded research, we need to be aware of the shifting science-policy environment.One more time, I have a reason to thank Mike Heroux, who took time for a video call with me as I prepared my SC20 invited talk. In his position as Senior Scientist at Sandia, 1/5 of his time is spent in service to the lab's activities, and this includes serving in the review committee of the internal Laboratory Directed Research & Development (LDRD) grants. As it is an internal program, the Calls for Proposals are not available publicly, but Mike told me that they now contain specific language asking proposers to include statements on how the project will address transparency and reproducibility. These aspects are discussed in the proposal review and are a factor in the decision-making. As community expectations grow, it could happen that between two proposals equally ranked in the science portion the tie-break comes from one of them better addressing reproducibility. Already some teams at Sandia are performing at a high level, e.g., they produce an Artifact Description appendix for every publication they submit, regardless of the conference or journal requirements.We don't know if or when NSF might add similar stipulations to general grant proposal guidelines, asking researchers to describe transparency and reproducibility in the project narrative. One place where we see the agency start responding to shifting expectations about open sharing of research objects is the section on results from prior funding. NSF currently requires here a listing of publications from prior awards, and "evidence of research products and their availability, including …data [and] software."I want to again thank Beth Plale, who took time to meet with me over video and sent me follow-up materials to use in preparing my SC20 talk. In March 2020, NSF issued a "Dear Colleague Letter" on Open Science for Research Data, with Beth then acting as the public access program director. The DCL says that NSF is expanding its Public Access Repository (NSF PAR) to accept metadata records, leading to data discovery and access. It requires research data to be deposited in an archival service and assigned a Digital Object Identifier (DOI), a global and persistent link to the object on the web. A grant proposal's Data Management Plan should state the anticipated archive to be used, and include any associated cost in the budget. Notice this line: "Data reporting will initially be voluntary." This implies that it will later be mandatory! The DCL invited proposals aimed at growing community readiness to advance open science. At the same time, the Office of Science and Technology Policy (OSTP) issued a Request for Information early this year asking what could Federal agencies do to make the results from research they fund publicly accessible. The OSTP sub-committee on open science is very active. An interesting and comprehensive response to the OSTP RFI comes from the MIT Libraries. It recommends (among other things): Policies that default to open sharing for data and code, with opt-out exceptions available [for special cases]… Providing incentives for sharing of data and code, including supporting credentialing and peer-review; and encouraging open licensing. Recognizing data and code as “legitimate, citable products of research” and providing incentives and support for systems of data sharing and citation… The MIT Libraries response addresses various other themes like responsible business models for open access journals, and federal support for vital infrastructure needed to make open access to research results more efficient and widespread. It also recommends that Federal agencies provide incentives for documenting and raising quality of data and code, and also "promote, support, and require effective data practices, such as persistent identifiers for data, and efficient means for creating auditable and machine readable data management plans."To boot, the National Institutes of Health (NIH) just announced on October 29 a new policy on data management and sharing. It requires researchers to plan prospectively for managing and sharing scientific data openly, saying: "we aim to shift the culture of research to make data sharing commonplace and unexceptional."Another setting where we could imagine expectations to discuss reproducibility and open research objects is proposals for allocation of computing time. For this section, I need to thank John West, Director Of Strategic Initiatives at the Texas Advanced Computing Center (and CiSE Associate EiC), who took time for a video call with me on this topic. We bounced ideas about how cyber-infrastructure providers might play a role in growing adoption of reproducibility practices. Currently, the NSF science proposal and the computing allocation proposal are awarded separately. The Allocation Submission Guidelines discuss review criteria, which include: intellectual merit (demonstrated by the NSF science award), methodology (models, software, analysis methods), research plan and resource request, and efficient use of the computational resources. For the most part, researchers have to show that their application scales to the size of the system they are requesting time on. Interestingly, the allocation award is not tied to performance, and researchers are not asked to show that their codes are optimized, only that they scale and that the research question is feasible to be answered in the allocated time. The responsible stewardship of the supercomputing system is provided for via a close collaboration between the researchers and the members of the supercomputing facility. Codes are instrumented under the hood with low-overhead collection of system-wide performance data (in the UT facility, with TACC-Stats) and a web interface for reports.I see three opportunities here: 1) workflow-management and/or system monitoring could be extended to also supply automated provenance capture; 2) the expert staff at the facility could broaden their support to researchers to include advice and training in transparency and reproducibility matters; and 3) cyber-infrastructure facilities could expand their training initiatives to include essential skills for reproducible research. John floated other ideas, like the possibility that some projects be offered a bump on their allocations (say, 5% or 10%) to engage in R&R activities; or, more drastic perhaps, that projects may not be awarded allocations over a certain threshold unless they show commitment and a level of maturity in reproducibility.Next steps for HPCThe SC Transparency and Reproducibility Initiative is one of the innovative, early efforts to gradually raise the expectations and educate a large community about how to address it and why it matters. Over six years, we have built community awareness, and buy-in. This year's community sentiment study shows frank progress: 90% of the respondents are aware of the issues around reproducibility, and only 15% thought the concerns are exaggerated. Importantly, researchers report that they are consulting the artifact appendices of technical papers, signaling impact. As a community, we are better prepared to adapt to raising expectations from funders, publishers, and readers.The pandemic crisis has unleashed a tide of actions to increase access and share results: the Covid-19 Open Research Dataset (CORD-19) is an example \cite{al2020}; the COVID-19 Molecular Structure and Therapeutics Hub at MolSSI is another. Facing a global challenge, we as a society are strengthened by facilitating immediate public access to data, code, and published results. This point has been made by many in recent months, but perhaps most eloquently by Rommie Amaro and Adrian Mulholland in their Community Letter Regarding Sharing Biomolecular Simulation Data for COVID-19—signed by more than a hundred researchers from around the world \cite{j2020}. It says: "There is an urgent need to share our methods, models, and results openly and quickly to test findings, ensure reproducibility, test significance, eliminate dead-ends, and accelerate discovery." Then it follows with several commitments: to making results available quickly via pre-prints; to make available input files, model-building and analysis scripts (e.g., Jupyter notebooks), and data necessary to reproduce the results; to use open data-sharing platforms to make available results as quickly as possible; to share algorithms and methods in order to accelerate reuse and innovation; and to apply permissive open-source licensing strategies. Interestingly, these commitments are reminiscent of the pledges I made in my Reproducibility PI Manifesto \cite{barba2012} eight years ago!One thing the pandemic instantly provided is a strong incentive to participate in open science and attend to reproducibility. The question is how much will newly adopted practices persist once the incentive of a world crisis is removed.I've examined here several issues of incentives for transparent and reproducible research. But social epistemologists of science know that so-called Mertonian norms (for sharing widely the results of research) are supported by both economic and ethical factors—incentives and norms—in close interrelation. Social norms require a predominant normative expectation (for example, sharing of food in a given situation and culture). In the case of open sharing of research results, those expectations are not prime, due to researchers' sensitivity to credit incentives. Heesen \cite{heesen2017} concludes: "Give sufficient credit for whatever one would like to see shared ... and scientists will indeed start sharing it."In HPC settings, where we can hardly ever reproduce results (due to machine access, cost, and effort), a vigorous alignment with the goals of transparency and reproducibility will develop a blend of incentives and norms, will consider especially the applications of high consequence to society, and will support researchers with infrastructure (human and cyber). Over time, we will arrive at a level of maturity to achieve the goal of trustworthy computational evidence, not by actually exercising the open research objects (artifacts) shared by authors (data and code), but by a research process that ensures unimpeachable provenance.

Hossein Firoozabadi

and 2 more

Bio-photovoltaic devices (BPVs) harness photosynthetic organisms to produce bioelectricity in an eco-friendly way. However, their low energy efficiency is still a challenge. A comprehension of metabolic constraints can result in finding strategies for efficiency enhancement. This study presents a systemic approach based on metabolic modeling to design a regulatory defined medium, reducing the intracellular constraints in bioelectricity generation of Synechocystis sp. PCC6803 through the cellular metabolism alteration. The approach identified key reactions that played a critical role in improving electricity generation in Synechocystis sp. PCC6803 by comparing multiple optimal solutions of minimal and maximal NADH generation using two criteria. Regulatory compounds, which controlled the enzyme activity of the key reactions, were obtained from the BRENDA database. The selected compounds were subsequently added to the culture media, and their effect on bioelectricity generation was experimentally assessed. The power density curves for different culture media showed the BPV fed by Synechocystis sp. PCC6803 suspension in BG-11 supplemented with NH4Cl achieved the maximum power density of 148.27 mW m-2. This produced power density was more than 40.5-fold of what was obtained for the BPV fed with cyanobacterial suspension in BG-11. The effect of the activators on BPV performance was also evaluated by comparing their overpotential, maximum produced power density, and biofilm morphology under different conditions. These findings demonstrated the crucial role of cellular metabolism in improving bioelectricity generation in BPVs.

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