Accurately conceptualizing 3D protein/ligand structures is thus vital to scientific research and education. Virtual reality (VR) enables protein visualization in stereoscopic 3D, but many VR molecular-visualization programs are expensive and challenging to use; work only on specific VR headsets; rely on complicated model-preparation software; and/or require the user to install separate programs or plugins. Here we introduce ProteinVR, a web-based application that works on various VR setups and operating systems. ProteinVR displays molecular structures within 3D environments that give useful biological context and allow users to situate themselves in 3D space. Our web-based implementation is ideal for hypothesis generation and education in research and large-classroom settings. We release ProteinVR under the open-source BSD-3-Clause license. A copy of the program is available free of charge from  http://durrantlab.com/pvr/.Proteins are microscopic machines that help maintain, defend, and regulate cells. Properly understanding the three-dimensional structures of these machines–as well as the small molecules that interact with them–can advance scientific fields ranging from basic molecular biology to drug discovery. Virtual reality (VR) is a powerful tool for studying protein structures. But many current systems for viewing molecules in VR, though effective, have challenging usability limitations. We have created a new web application called ProteinVR that overcomes these challenges. ProteinVR enables VR molecular visualization in users’ browsers, without requiring them to install a separate program or plugin. It runs on a broad range of desktop, laptop, and mobile devices. For users without VR headsets, ProteinVR leverages mobile-device orientation sensors or video-game-style keyboard navigation to provide an immersive experience. We release ProteinVR as open-source software and have posted a working version at  PLOS Computational Biology Software paper.This is a Molecular visualization can provide structural, biological, and pharmacological insights that cannot be obtained in any other way. Traditionally, researchers and educators have used 2D schema  to represent molecular structures . CarefulVirtual reality (VR) overcomes these limitations by displaying models in stereoscopic 3D. Users are thus able to better perceive the spatial arrangements of protein binding pockets and protein/ligand interactions –13. CompIn the past, the high cost of VR hindered efforts to popularize true 3D visualization systems  , 15. ButWe here present ProteinVR, a new open-source system that leverages these recent advances in VR to better visualize proteins and protein/ligand complexes . Proteinhttp://durrantlab.com/protein-vr/, and a working version of the app can be accessed at http://durrantlab.com/pvr/.ProteinVR will be a useful tool for both the research and educational community. It allows researchers to better examine molecular structures and to collaboratively share molecular visualizations via convenient public URLs. It also allows educators and outreach-program coordinators to easily share instructive 3D scenes with students and the broader public. We release ProteinVR under the terms of the open-source BSD-3-Clause license. A copy is available free of charge from ProteinVR leverages new and emerging technologies such as 3D web graphics and VR headsets to display relationships between molecular components in full 3D . It is wProteinVR uses 3Dmol.js  to generTo provide context and to orient the user in 3D space, ProteinVR positions molecular models within 3D environments . We usedTo accommodate a broad range of devices, several simple default environments are included in the ProteinVR download. These environments ensure that ProteinVR can operate “out of the box” on even low-powered  devices and VR headsets. The scenes consist of only a skybox . Two-dimensional pictures of distant objects are projected onto the cube faces to suggest a larger surrounding environment. ProteinVR includes skybox-based environments that depict the inside of a blood vessel, the lipid-bilayer surface of a cell, and the intracellular space . For casProteinVR’s web-based approach has many advantages. First, ProteinVR uses native web technologies, so it does not require users to download or install any programs or plugins beyond the web browser itself. In this sense it differs from other VR molecular-visualization programs , 19–22, Second, our web-based approach ensures broad compatibility. ProteinVR is built using BabylonJS, a free, open-source game engine compatible with all modern web browsers. Such web browsers are available on all major platforms, including various operating systems . BabylonJS also ensures compatibility with a broad range of computer-hardware setups . Where VR is available, ProteinVR uses BabylonJS to leverage many different kinds of VR headsets. Where VR is not available, ProteinVR uses other hardware  to provide as immersive an experience as possible.Beyond ensuring broad compatibility, BabylonJS also helps future-proof ProteinVR. ProteinVR uses BabylonJS to access the underlying WebVR API. This API is subject to ongoing changes—so much so that it may soon be replaced by an entirely new API (WebXR) that additionally enables augmented reality (AR). The BabylonJS community actively updates the game-engine code so that BabylonJS-powered software such as ProteinVR need not be entirely rewritten every time the API changes.When users first open ProteinVR, the application displays the default molecule NanoKid  Fig 1)..Fig 1). Several 2D buttons appear on the right of the screen that are only accessible when not in VR mode . The firThe same menu for changing the molecular style and rotation  is also At the top-most level, the ProteinVR menu is divided into two broad categories . The “RoProteinVR also makes it easy to save molecular scenes with custom visualizations such as these. Every time a molecular representation is loaded, rotated, or otherwise altered, ProteinVR updates the browser URL to track the change. Copying the URL at any point into a new browser tab–even on a different device–recreates the exact same ProteinVR scene.Interested readers may wish to view To accommodate a broad range of devices, ProteinVR runs in four modes: VR mode, device-orientation mode, desktop mode, and leader mode. In all four, ProteinVR uses video-game-style navigation. Objects reside at fixed positions in a 3D environment, and the camera moves (or teleports) to different locations in the scene.VR mode is ideal when users have access to a VR headset . This mode provides a fully immersive experience wherein users can view their molecular structures in stereoscopic 3D. The 3D environments are particularly useful in VR mode, as they improve the sense of immersion. By allowing viewers to orient themselves spatially, 3D environments may also reduce VR sickness , which iIn VR mode, users can look about the scene by physically moving their heads. Some VR headsets also allow users to navigate to nearby locations by physically moving about the room. Teleportation navigation enables movement to distant points in the virtual world . A simplVR controllers with trackpads or joysticks enable more fine-grained movements . To slowWe have specifically tested VR-mode on the operating-system, web-browser, and VR-headset setups indicated in Desktop computers.We have verified that VR mode works well on Windows 10. We currently recommend the Firefox web browser. We have struggled to enable VR on Windows 10 Google Chrome, though we expect continued improvements in future versions given the expanding popularity of VR. Fortunately, Firefox provides a stable WebVR implementation that is enabled by default.VR support in macOS is currently limited, though Apple has plans to expand support in the future. In preliminary tests, we did once manage to get WebVR working  on an HTC Vive connected to a MacBook Pro with an external graphics card. But we have not been able to reproduce that preliminary success and so cannot currently recommend macOS for VR.Mobile devices.VR mode also works well on most mobile devices. The WebVR API on Android is easy to access. In contrast, WebVR access on iOS is currently challenging. iOS mobile Safari does not allow webpages to hide the browser address bar, as required for VR visualization using mobile  headsets. Additionally, iOS does not allow the mobile Safari browser to access the device’s orientation sensors by default, making it impossible for ProteinVR to respond to head movements. Apple requires all third-party browsers on iOS  to use the same WebKit framework and JavaScript engine that Safari does, so it is not currently possible to overcome these challenges by switching to another browser.To eliminate the address bar on iOS, users should install ProteinVR as a progressive web app (PWA). PWA installation places a ProteinVR icon on the device’s home screen and allows ProteinVR to run in full-screen mode. Simply visit the ProteinVR website via mobile Safari and use the browser’s “Share > Add to Home Screen” menu item. Additionally, users must enable access to the device-orientation sensors (even if running ProteinVR as a PWA) via Settings > Safari > Motion & Orientation Access. We are hopeful that Apple will simplify this process in the future as it expands its VR support.VR controllers.We have found that WebVR occasionally fails to recognize connected VR controllers. Users who struggle with the controllers may find the following tips helpful:before entering VR.Turn on the controllers On VR systems with multiple controllers , turn on all controllers, even though teleportation navigation requires only one.When using the Oculus Go headset (Oculus Browser), enter VR mode, press the Oculus button, and select the “Resume” menu item to force controller recognition.Device-orientation mode is ideal when viewing ProteinVR scenes on mobile devices with orientation sensors. If ProteinVR detects such sensors, it automatically updates its viewport to match the orientation of the device itself. Users can thus view their molecular structures from different angles by physically reorienting their devices. ProteinVR also uses teleportation navigation in device-orientation mode. A navigation sphere (placed in the direction the mobile device is pointing) indicates the current teleport destination. To teleport to the location of the sphere, the user simply taps on the mobile-device screen.We have specifically tested device-orientation mode on the operating-system/web-browser combinations indicated in If neither a VR headset nor an orientation sensor is available, ProteinVR runs in desktop mode. Desktop mode uses a standard keyboard-and-mouse navigation system similar to that commonly used in video games. The arrow keys (or WASD keys) move forward, backward, and sideways. Clicking and dragging with the mouse changes the viewing angle. If the user clicks on the full-screen button in the main window , ProteinWe have specifically tested desktop mode on the operating-system/web-browser combinations indicated in Finally, ProteinVR can run in “leader mode.” This mode transforms the program into a powerful presentation tool. In many scenarios, multiple users may wish to visualize the same ProteinVR scene together. For example, a presenter may wish to use VR navigation to illustrate a specific molecular structure while simultaneously projecting the same view onto the screen behind her. Similarly, a teacher may wish to visualize a specific protein/ligand interaction using an advanced VR headset  while his students view the same interaction on their phones.A technology called WebRTC enables direct communication between leader and follower instances. When running in “leader” mode, ProteinVR broadcasts the user’s location in the 3D scene, as well as information about how the molecule of interest is currently represented. Broadcasting is available from VR headsets, Android phones, laptops, and desktops . Safari http://durrantlab.com/pvr/). We encourage users to explore the app directly to better appreciate the benefits of our approach.It is challenging to fully grasp the advantages of VR without entering the virtual world. Fortunately, the ProteinVR web app is easily accessible  bound to compound V2, a low-micromolar naphthalene-based inhibitor [Trypanosoma brucei [First, we considered applications to rational ligand design. We examined nhibitor . REL1 isa brucei . It is aa brucei –31. REL1a brucei .http://mgltools.scripps.edu/), and AutoDock Vina [We used Gypsum-DL , MGLToolock Vina  to dock ock Vina  and Protock Vina  cannot pViewing the same protein/ligand complex in ProteinVR with an HTC Vive VR headset was more intuitive. The molecular structure had presence. With almost no effort, the tester was able to see that the two phosphate groups of the ligand flank a positively charged arginine residue, that other positively charged residues may contribute to molecular recognition via electrostatic interactions, that ligand hydroxyl groups form hydrogen bonds with the protein, etc. It was also immediately clear that the Vina-predicted ligand pose may be incorrect. One of the naphthalene moieties could more optimally participate in a π-π stacking interaction with the protein if rotated slightly, and a buried amino moiety appears to have no hydrogen-bond partner. The ability to look around obstructing atoms with simple head movements, together with true stereoscopic depth perception, made obtaining these kinds of insights particularly intuitive.This test case illustrates how ProteinVR can benefit both researchers and educators. We have spent many hours analyzing protein/ligand complexes using non-VR programs. These programs are effective, but they require users to trick their brains into a kind of faux depth perception by using fog and perspective view, and by rocking the molecular structures about carefully selected pivot points. Seeing the structures in stereoscopic 3D substantially reduces the cognitive load required to appreciate these interactions, ultimately speeding analysis. Students in particular stand to benefit from the VR approach. Perceiving the 3D geometry of the bound ligand pose becomes intuitive, allowing students to focus on the meaning of the interactions rather than the presentation.As a second test case, we used ProteinVR to reexamine a previously published molecular-dynamics (MD) simulation . The simReexamining these pocket conformations with ProteinVR on an HTC Vive VR headset allowed for a far more intuitive analysis. ProteinVR does not yet support MD-trajectory visualization, but it was not difficult to concatenate the largest- and smallest-pocket conformations into a single PDB file and to assign different chain IDs to each. We loaded this two-structure PDB file into ProteinVR and applied a differently colored surface representation to each conformation. To better appreciate the pocket-volume difference, we attempted to position the ProteinVR camera between the surfaces of the smallest-volume (collapsed) and largest-volume (open) pockets.Before entering VR mode, it was difficult to observe this inter-surface space  from within. As with other non-VR programs, camera-adjacent surface sections were often clipped . In contThis test case similarly illustrates how ProteinVR can benefit both researchers and educators. Rational ligand design often requires a thorough appreciation of the 3D volume that a binding pocket occupies. But visualizing narrow and/or buried pockets is sometimes difficult without VR. In contrast, ProteinVR in VR mode enables minute movements by tracking head motions. Both researchers and students can easily avoid clipping while looking about pocket interiors. The stereoscopic vision possible in VR also give a better sense of the pocket dimensions.ProteinVR makes setting up VR molecular visualizations particularly easy. In contrast, some other VR programs rely on complex software pipelines that require users to install (and master) third-party modeling programs such as Blender (Blender Foundation) and Unity (Unity Technologies). Users must setup molecular representations  during the initial modeling stage, making it impossible to change the representation in real-time VR.The open-source BlendMol  plugin fRealityConvert , like BlA number of desktop applications enable VR molecular visualization directly, without requiring a complex pipeline. These desktop programs often limit their compatibility to high-end VR devices , 41, 42.in silico mutagenesis). The free version of Nanome does come with some important limitations, however. For example, VR molecular scenes created with the free version are entirely public. In fact, as we were testing Nanome, another user joined our room and was able to observe our activities.That having been said, desktop programs that cater to high-end VR headsets are able to implement useful features that ProteinVR currently lacks. Molecular Rift  is a gooRecognizing the advantages of the web-based approach, others have also explored online VR molecular-visualization systems , 43. OneThe Unity game engine (Unity Technologies) warrants specific mention because it powers several desktop VR applications, including Molecular Rift , describUnity has several advantages over the BabylonJS game engine behind ProteinVR. Its advanced editor greatly simplifies development, and its online community has developed many add-ons  that allow developers to easily add the specific features that their application requires. If desktop Unity applications are properly optimized, their performance also surpasses that of any web-based app because most browsers cap graphics updates at 60 frames per second. Finally, because the WebVR standard is still evolving, Unity applications are arguably more stable, at least for the time being.Despite these advantages, we built ProteinVR using BabylonJS because it is particularly well suited for web apps. Unity applications can be compiled to run in the browser, but they are almost always far larger than the equivalent BabylonJS app, requiring more time and bandwidth to download. Unity also lacks official support for browser-based apps on mobile devices, and the BabylonJS approach to WebVR is much more straightforward than its Unity counterpart. Because BabylonJS is itself written in JavaScript, integration with web technologies such as WebRTC and the HTML5 DOM  is also much easier. Finally, the Unity engine is closed source, and free use requires Unity-specific branding.http://durrantlab.com/protein-vr/. The accompanying documentation includes instructions for using and compiling the software. Most users will prefer to simply access the working version we have posted at http://durrantlab.com/pvr/. Users may also report bugs or other issues via the online forum at http://durrantlab.com/forums/forum/protein-vr/.We release ProteinVR under the open-source BSD-3-Clause license. The source code can be downloaded anonymously from our public repository at ProteinVR’s strength lies in its simplicity. We are eager to avoid “feature creep,” wherein excessive software updates add only minor benefit while complicating use. Other programs exist for model building and analysis. ProteinVR is meant to be a molecular viewer. Future improvements will further enhance that core functionality.For example, several related programs display molecules using AR. Unlike VR, AR positions virtual objects in the context of the actual world . Some studies suggest that AR helps mitigate VR sickness , 45, 46,One desktop VR program called NarupaXR allows users to interact with real-time atomic-resolution MD simulations running on remote computer resources , 47–49. Additional planned features include 1) improved chain and residue labeling, 2) automatic detection and visualization of protein/ligand interactions via our BINANA algorithm , and 3) Further user testing will evaluate how best to deploy ProteinVR in research and educational settings. Continued use in our lab–together with feedback from our users–will help us further evaluate ProteinVR’s utility in a research context. Members of well funded research labs with dedicated space for VR visualization may prefer desktop applications running on powerful computers with high-end VR headsets. These programs offer an impressive array of features that are difficult to deliver over the web. But in many situations, ProteinVR’s convenience  may make it the preferred choice.We expect that ProteinVR’s portability, broad hardware compatibility, and ease of deployment will be particularly useful in an educational context. Lecturers are rarely able to bring an expensive gaming computer with a high-end VR headset to class. And even when such a system is available, it cannot reasonably accommodate large classrooms. In contrast, purchasing low-end VR headsets  so students can view VR scenes on their mobile devices is feasible. A limited number of medium-quality headsets  can then supplement the mobile-based devices.Published studies have shown that VR enhances science education generally  and chemS1 Video(MP4)Click here for additional data file.S1 Fig(PDF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.


Spatiotemporal molecular medicine is a new discipline of medicine to precisely understand the pathogenesis, history, and epidemiology, and aims to achieve prevention, diagnosis, and therapy at molecular levels for human diseases in multidimensional aspects related to a spatial and temporal context. The human body is a three‐dimensional object with the space of length, width, and height, while the spatiotemporal concept demonstrates a four‐dimensional continuum with the concept of time. Clinical spatialization of a disease should be considered at the levels of genetics , populations , and individuals . Clinical temporalization covers the historical process and progression of disease occurrence and development, duration‐based alteration of clinical phenomes, and dynamics of patient responses to therapy. Clinical trans‐omics was proposed as a new approach to understand the disease from the cross‐points among different layers of networks generated from the integration of clinical phenomics with molecular multi‐omics.Spatiotemporal molecular omics are a major part of spatiotemporal molecular medicine. For example, transcriptomic profiles of tissues, isolated single category of cells, or single cells demonstrate tissue‐ or cell‐specific transcriptional function as one‐dimensional information of mRNA expression. Ståhl et al. labeled arrayed reverse transcription primers with unique barcodes, in situ hybridized positioning mRNA on tissue sections with those primers, as well as visually and quantitively imaged and analyzed transcriptomic profiles on tissue surface, coined as spatial transcriptomics, in order to define the exact position of transcriptional alterations with the tissue and cells.Spatiotemporal molecular medicine has a high scientific impact on investigation of cell–cell communication, microenvironmental function, and interactomes. The interaction networks of genes, proteins, and cells within the microenvironment play a decisive role in the production of chemoattractants for inflammatory cell recruitment and growth factor production for cancer cell extensions. For example, the liver microenvironment was considered as one of the easy locations for extrahepatic tumor metastasisSpatiotemporal molecular medicine has the special power to explore molecular mechanisms and modifications of embryonic development, tissue morphogenesis, and organogenesis. Genomic dimensions, architectures, and organization play critical roles in regulations of gene transcription, spatiotemporal development, genome assembly, and target‐based therapy.Spatiotemporal medicine exists in clinic diagnosis, therapy, and prognosis for decades. The process of clinically examining responses of different organs to pathogens, diseases, and therapies at various stages and durations per se is a spatiotemporal course. Spatiotemporal images of organ can be constructed using ultrasounds, computed tomography (CT), nuclear magnetic resonance/CT, positron‐emission tomography/CT, or pathological sections. Of those, four‐dimensional ultrasound using spatiotemporal image correlation with software allows for detection of organ anatomy and function during aging and has special impact in disease diagnosis. Fluorescence endomicroscopy with automated image analysis can produce large quantities of data on the spatiotemporal behavior of target gene expression in cells of human digestive and respiratory tissues to analyze the geometry and fluorescence image and monitor temporal changes in gene expression. The temporal notion of causality between clinical phenomes observed over a period of time  becomes an important part of spatiotemporal medicine, as suggested by considering shorter and longer time‐series.Spatiotemporal molecular medicine contains an additional molecular level on top of spatiotemporal medicine and becomes appliable in clinical practice and investigation with the development of molecular barcode labeling technologies. Advanced methods to detect the spatial positioning of mRNA and protein expression in specific cells in tissue sections provide a new opportunity for defining the exact locations of disease‐, disfunction‐, signal‐, and regulation‐specific alterations in pathological conditions. This makes it possible to identify DNA methylation and transcriptomic information with protein expression in the immunophenotyping of cells on pathological images of ultrasounds and CT in the future, although many challenges remain to be overcome. The integration of spatiotemporal medicine with molecular spatial‐omics maps can provide new strategies for early diagnosis and individualized therapies at molecular levels. The methodologies to merge image profiles and clinical phenomes with molecular profiles include in situ hybridization/fluorescence staining with oligonucleotide probes, digital barcodes tag with oligonucleotides, DNA microscopy with chemical DNA reactions fluorescent barcoding with sequencing, Drop‐seq technology integrating single‐cell RNA sequencing and imaging, padlock amplification of gene sequencing, cryogenic tissue sections with RNA sequencing and spatial data, cryogenic tissues from laser capture microdissection and RNA sequencing, cDNA synthesis in situ with spatial barcoding and RNA sequencing, mRNA barcoded in situ with spatial sequencing by oligonucleotide ligation and detection, virtual reconstruction of the tissue from single‐cell RNA sequencing, and new transcriptome alkylation‐dependent single‐cell RNA sequencing to identify temporal and spatial features of single‐cell data.Spatiotemporal molecular medicine is a part of molecular medicine characterized by gene‐based diagnosis and therapy. With the improvement of on‐/off‐target site specificity and efficiency and improved understanding of structures, mechanisms, clinical applications, and off‐target activities of genome editing systems, genome editing will become one of the clinical precision medicine strategies and multidisciplinary therapy strategies by integrating gene sequencing, clinical trans‐omics, and single‐cell biomedicine.Spatiotemporal molecular medicine requires the obvious contributions from rapid development of artificial intelligence, automatic robots, and computational and mathematical models. For example, the artificial intelligent cell was proposed as a system with computerized databases, digitalized informatics of biological elements, and programmed function and signals at a single‐cell level.In conclusion, we propose the concept of spatiotemporal molecular medicine as a new discipline of medicine and believe it will become more important and applicable with advanced development of spatial and temporal transcriptomics, proteomics, and metabolomics. Clinical spatialization and temporalization of phenomes are integrated with the information from spatiotemporal molecular omics to form a four‐dimensional understanding, diagnosis, and therapy for patients. Spatiotemporal measurements and analyses are decisive factors that may limit clinical applications of spatiotemporal molecular medicine. Although many challenges need to be overcome, spatiotemporal molecular medicine will improve our knowledge of diseases, provide multidimensional and targeted panels for more precise and early diagnosis and therapy, and be one of the future topics in clinical and translational medicine.


Staphylococcus aureus) bacteria and Gram-negative (Escherichia coli) bacteria. The developed nanofibers had high profile antibacterial activity against both bacteria, but showed excellent results against S. aureus bacteria as compared with E. coli. These nanofibers have potential applications in the development of surgical gowns, gloves, etc.In the present condition of COVID-19, the demand for antimicrobial products such as face masks and surgical gowns has increased. Because of this increasing demand, there is a need to conduct a study on the development of antimicrobial material. Therefore, this study was conducted on the development of Aloe Vera and Polyvinyl Alcohol (AV/PVA) electrospun nanofibers. Four different fibers were developed by varying the concentrations of Aloe vera  while maintaining the concentration of PVA constant. The developed samples were subjected to different characterization techniques such as SEM, FTIR, XRD, TGA, and ICP studies. After that, the antimicrobial activity of the developed Aloe Vera/PVA electrospun nanofibers was checked against Gram-positive ( Escherichia coli and Staphylococcus aureus bacteria by allowing 18 h contact of nanofibers with bacteria. By using 1% Ag loaded nanofibers, a 14.4 mm zone of inhibition was observed against S. aureus and 16 mm against E. coli [P. aeruginose and 50% reduction of S. aureus bacteria [E. coli and S. aureus bacteria. They found that 450 μg/mL concentration of CuO-ZnO loaded electrospun nanofibers showed inhibited growth against E. coli bacteria, whereas 300 μg/mL concentration CuO-ZnO loaded electrospun nanofibers showed inhibited growth against S. aureus bacteria [S. aureus bacteria [S. aureus) by using nisin/cellulose acetate electrospun nanofibers [S. aureus and pseudomonas aeruginosa bacteria. For nanofibers loaded with broad leaves oils, the inhibition zone was shown to be 10 mm against P. aeruginosa and 19 mm against S. aureus, whereas for nanofibers loaded with narrow leaves oil, the zone of inhibition was show to be 8 mm against Pseudomonas aeruginosa and 15 mm against S. aureus bacteria. They concluded their study by saying that oils of broader leaves show higher antibacterial activity as compare with oils of narrow leaves [Considering the current situation due to the pandemic of COVID-19, people feel insecure about the products they are using in their daily life. Therefore, the demand for antimicrobial products is increasing day-by-day. In such a situation, nanotechnology can play a vital role in the development of antimicrobial products . Nanotec E. coli . A similbacteria . P. Gopibacteria . Differebacteria . Han et nofibers . Sadri ew leaves ,32. Aloew leaves . Many rew leaves ,37,38,39w leaves . Numerouw leaves . Similarw leaves . Sirdha w leaves . Abdullaw leaves . Jegina w leaves . FatemahE. coli and S. aureus bacteria.A lot of research has been conducted on the loading of Aloe Vera gel with different polymers for different applications, however, very little literature has been found on the loading of Aloe Vera gel with Polyvinyl Alcohol (PVA) for rapid antibacterial applications. The authors have been the first to perform antibacterial activity of AV/PVA nanofibers. Therefore, there is a need to further explore this area of research. This study focused on the development of Aloe Vera/PVA electrospun nanofibers by using the electrospinning technique. Four different concentrations of Aloe Vera gel were used for the development of electrospun nanofibers. The developed nanofibers were tested for the antimicrobial activity against Polyvinyl Alcohol (PVA)  was purchased from the Sigma-Aldrich Corporation , Aloe Vera gel was extracted from Pakistani Aloe Vera plant and glutaraldehyde  was provided from MP Biomedical . Deionized water was used.Four different solutions were formed by varying the concentration of Aleo vera gel, i.e., 0.5%, 1%, 2.5%, and 3%. A certain amount of distilled water was taken in the reagent bottle, then, 10% (W/V) PVA powder was added slowly to this water and stirred at 450 rpm. The temperature was slowly raised, up to 60 °C, and then stirred for about 90 min, until a clear solution was obtained. Then, 0.5% of Aleo vera (AV) gel was added slowly to this solution and stirred for about 90 min, at 500 rpm, while maintaining the temperature at 60 °C. After some time, a clear solution of AV/PVA of certain viscosity was obtained. Similar steps were followed for the formation of the other three solutions with different concentrations of Aleo vera gel. The flow diagram of the solution formation process is shown in For the production of AV/PVA electrospun nanofibers, a syringe was filled with the prepared polymer solution and attached to an electrospinning machine, and a voltage of 17 kV was applied, while maintaining a distance of 20 cm between the collector and the tip of the syringe. As the voltage was applied, the AV/PVA fibers started to be generated and were collected on the collector of the electrospinning machine. The resultant nanofibers were cross linked by the hydrochloric acid (HCL) foaming of AV/PVA/GA at 30 °C, for 60 s. In this reaction, GA and HCl acted as a chemical crosslinking agent and a catalyst, respectively, as shown in Prepared electrospun nanofibers were subjected to certain characterization techniques to test the certain characteristics of the prepared electrospun nanofibers. To check the surface morphology of the electrospun nanofibers, nanofibers were analyzed by using a scanning electron microscope (SEM) JSM-5300, JEOL Ltd., Tokyo, Japan. The XRD analysis of AV/PVA electrospun nanofibers was performed at 25 °C with nanofiber samples using a Rotaflex RT300 mA  and nickel-filtered Cu. Ka radiation was used for measurements, along with an angular angle of 5 ≤ 2θ ≤ 50°. To test the chemical interactions, the analysis of the prepared electrospun nanofibers were studied by FTIR spectra . The water contact angle measurements were done using a contact angle meter . Five different specimens of each sample were tested and investigated. Inductively coupled plasma atomic emission spectroscopy  was implemented to determine AV release in solutions, for up to 72 h.E. coli) and Gram-positive bacteria (S. aureus). Both bacterial strains were incubated overnight at a temperature of 37 °C. Then, 45 μL of a 105 dilution of stain solution was spread on sterilizing agar plates. Samples were placed transversely on the agar surface to ensure intimate contact. Then, the growth was examined, and the inhibition zone was calculated by using Equation (1) [The antimicrobial activity of all the developed samples was analyzed by using the agar diffusion test . For this purpose, the AATCC-147 standard method was used, and a triplication process was adopted. The AV/PVA electrospun nanofibers were tested against Gram-negative bacteria (tion (1)  and withAll the developed samples with Aloe Vera concentration  and neat PVA nanofibers were analyzed by SEM for surface morphology analysis. Five images from different places of a same sample were investigated and it was confirmed that all the fibers were smooth and there was no formation of beads that took place, as mentioned in To analyze the diameter of the prepared electrospun nanofibers, ImageJ software was used. A total of 200 readings were taken from each sample to calculate the average diameter of electrospun nanofibers. −1 to 4000 cm−1. Pure Aloe Vera sperctrum shows four main peaks. The peak at 1853 cm−1 corresponds to the amid group. The characteristic peak appears at 2247 cm−1, and 2477 cm−1 corresponds to the corboxylic functional group. However in the pure Aloe Vera spectra, the broader peaks in the range 3000–3600 cm−1 correspond to the presence of the –OH functional group. All other spectra shown in the figure are almost similar to each other, with a slight shifting of peaks. In all spectra, there is a broader peak that appears in the range 3300–3500 cm−1, which represents the phenolic functional groups, especially anthraquinones. The peaks that appear in the range 2900–3000 cm−1 are due to the C–H stretching, such peaks correspond to points 2938, 2920.4, 2936.1, 2335, and 2918.4 cm−1 in the case of pure PVA, 0.5%, 1.5%, 2.5%, and 3% AV/PVA electrospun nanofibers, respectively. In the spectra, peaks in the range 1030–1150 cm−1 are due to C-O stretching. Such peaks appear at points 1105, 1097, 1101.8, 1094.9, and 1091.8 cm−1 in the case of pure PVA, 0.5%, 1.5%, 2.5%, and 3% AV/PVA electrospun nanofibers, respectively. Due to C=O stretching, the peaks appear at points 1740, 1738, 1740.2, 1737, and 1734.1 cm−1 for pure PVA, 0.5%, 1.5%, 2.5%, and 3% AV/PVA electrospun nanofibers, respectively. C=C stretching in alion and vinyl ether components are shown in the range 1400–1500 cm−1 and correspond to points 1437, 1435.2, 1435.5, 1428.6, and 1429.3 cm−1 for pure PVA, 0.5%, 1.5%, 2.5%, and 3% AV/PVA electrospun nanofibers, respectively [−1 for all spectra are due to –OH bending in the phenolic group. The peaks appear between 790 and 840 cm−1 and correspond to C=C bending in the alkene group for all the spectra. From all the spectra, it can be concluded that there is no chemical interaction that takes place between Aloe Vera and PVA because no new peaks appear in the spectra. In the spectra, the broader peaks in the range 3300–3500 cm−1 indicate that the quantity of OH−1 groups increased with an increase in the quantity of Aloe Vera, as a result, the moisture-absorbing capacity of the material increased [ectively ,49. The ncreased .In order to investigate the hydrophilic behavior of the PVA and AV/PVA nanofibers, water contact analysis was done, as mentioned in the In order to investigate the release behavior of loaded AV in the AV/PVA nanofibers, as shown in In order to investigate the degradation profile of AV/PVA nanofibers, TGA analyss was performed, as shown in the Staphylococcus aureus and Escherichia coli. The antimicrobial activity is due to anthraquinones, pyrocatechol, isolated from the exudate of Aloe Vera [E. coli bacteria. It can be seen that at 0.5% concentration of AV the zone of inhibition for Trials 1–3 was calculated as 6.6, 6.8, and 7 mm, respectively. All three trials show antibacterial activity with slight variation in the zone of inhibition. It can also be seen that as the concentration of AV increase, the antibacterial activity of the nanofibers also increases. At 3% higher, antibacterial activity was observed with a zone of inhibition value of 10.5 mm , 10.79 mm , and 11.08 mm . S. aureus bacteria. Minimum activity was found at 0.5% AV concentration, with the zone of inhibition 7.8 mm , 7.86 mm , and 8.12 mm . Maximum activity was found at 3% AV concentration, with zone of inhibition 11.9 mm , 12.1 mm , and 12.3 mm . It can also be concluded from the results that nanofibers show excellent antibacterial activity against S. aureus bacteria as compare with E. coli. The possible reason behind this could be that the cell membrane of E. coli is thicker than that of S. aureus bacteria [AV/PVA electrospun nanofibers were screened to determine the antimicrobial activity of the resultant nanofibers. loe Vera . The cinloe Vera . When thloe Vera . Three tbacteria .−1 also increased, hence the tendency of the material to absorb moisture increased. The XRD analysis confirmed that by increasing the concentration of Aloe Vera, there was an increase of the amorphous regions in the AV/PVA electrospun nanofibers. The TGA spectra confirmed that the developed web for protective clothing had a suitable profile of thermal stability and a loaded amount of AV. In addition, the ICP study confirmed that AV had a very slow release behavior, which is appreciable for protective clothing. The antimicrobial activity of AV/PVA electrospun nanofibers is excellent, and therefore these fibers are best suited for the preparation of protection clothes  used against COVID-19. From the antimicrobial results, it can also be concluded that AV/PVA shows the highest antimicrobial activity against S. aureus as compare with E. coli bacteria.This study focused on the development of four different types of AV/PVA  electrospun nanofibers. The SEM analysis confirmed that all the developed fibers were smooth and bead free. At a higher concentration of Aleo vera, finer fibers were obtained. The FTIR analysis of the developed samples confirmed that there was no chemical interaction took place between Aloe Vera and PVA, and as a result no new peak appeared in the spectra. From the FTIR results, it was also concluded that as the concentration of Aleo vera increased, the quantity of OH


The naming of diseases is a critical aspect of public health communication. In light of the recent renaming of the ‘Wuhan novel coronavirus’ to COVID-19, the names of other health threats must be reviewed. In particular, a new name is urgently needed for the global challenge typically referred to as ‘antimicrobial resistance’. The current name is inconsistently used, difficult to pronounce and lacks meaning for lay audiences. It also fails to express the magnitude of the phenomenon’s potential consequences for human medicine. This article reviews and evaluates key findings from several cross-disciplinary streams of research on the psycholinguistic properties of names. These include early psychology literature pertaining to the concept of ‘word attensity’, recent cognitive research on ‘processing fluency’ in the context of word recognition, and relevant marketing literature examining the components of successful branding strategies. Three key criteria—pronounceability, meaningfulness and specificity—are found to influence the perception of names and these are discussed in the context of antimicrobial resistance. The article demonstrates that the current term of ‘antimicrobial resistance’ falls short with regard to all three criteria and concludes with specific recommendations for the creation of a new name. Only the strategic choice of a single term that is (i) short and easy to pronounce; (ii) intuitively meaningful to lay audiences and indicative of the existential threat linked to antimicrobial resistance; and (iii) uniquely associated with the topic of antimicrobial resistance is likely to bring about overdue change in the global discussion of antimicrobial resistance. In February 2020, the WHO announced an official name for a rapidly spreading viral disease. The disease, which had previously been referred to as ‘nCoV-2019’ or simply ‘Wuhan novel coronavirus’ was renamed to ‘COVID-19’.nomen est omen—originally attributed to Roman playwright Plautus—proclaims a causal link between a person’s name and their destiny.Identifying suitable names for public health threats is a key prerequisite for successful science communication with lay audiences. The significance of names has long been recognized in popular culture. Bemoaning the tragic consequences of her lover’s family name, Shakespeare’s Juliet famously exclaimed: ‘What’s in a name?’ Similarly, the Latin proverb Despite the overwhelming evidence on the importance of names, the scientific community continues to fall short in the coining of successful terminology to disseminate scientific discoveries about diseases or raise awareness about global challenges. One such challenge is antimicrobial resistance (commonly abbreviated as AMR).By 2050, more people will die from antimicrobial resistance (AMR) than currently die from cancer.,Given the undebatable importance of the problem, AMR continues to receive astonishingly little media coverage.Another challenge for successful AMR communication is its name and all related terminology. This includes ‘antimicrobial stewardship’—a term broadly referring to measures aimed at reducing the overuse of antimicrobial agents, which is difficult to understand for prescribers, let alone the general public. Also problematic is the common yet ambiguous term ‘antibiotic’ that is often used to mean ‘antibacterial agent’ and might be contributing to the public confusion about the role of ‘antibiotics’ for treating bacterial versus viral infections. To help communicate a large range of subtly different, yet interrelated, concepts, there appears to be a need for a whole new public language related to the global health challenge of AMR.Given the scope of this short review, however, the remainder of the article will focus on specifically evaluating the central term ‘antimicrobial resistance’. In this context, the UK Wellcome Trust Initiative ‘Re-branding Resistance’ has made important contributions by outlining the problematic inconsistency of the name when disseminating information about AMR.Consistency undoubtedly plays a crucial role in successful communication. However, other aspects such as the psycholinguistic properties of a name are just as likely to influence public awareness and understanding. The importance of such properties has been demonstrated by research from the scientific fields of linguistics, marketing and psychology, which attests to the existence of measurable features shaping the subjective experience of different names.,Stemming from a body of fundamental psychology research from the 1960s, the term ‘attensity’ was introduced to describe a word’s potential to engage people, capture their attention and improve subsequent memory of the word.Pronounceability refers to the ease of verbalizing a word, with research showing that words of higher pronounceability are processed more quickly,Meaningfulness and concreteness describe a word’s power to associate meaning. This may include the ease with which related mental images are retrieved or the availability of meaningful context to make sense of the word.,,,An updated and more comprehensive perspective on word attensity was provided by recent research on so-called processing fluency. The term refers to a subjective feeling of ease experienced when processing a stimulus such as a written word, and is often related to shorter reading or response times.The concept of processing fluency is frequently applied to design materials for less proficient readers  pronounceability and readability, referring to the name’s lexical attributes ; (ii) meaningfulness, concreteness and memorability, referring to a name’s power of evoking intuitive context and meaning; and (iii) specificity and uniqueness, referring to a word’s unambiguous meaning and novel linguistic aspects.Unfortunately, the name ‘antimicrobial resistance’ appears to fall short when measured against all these criteria and this might explain why the term fails to capture and sustain the international attention it beckons. The full term ‘antimicrobial resistance’ is characterized by a high word length of nine syllables, which is difficult to pronounce and contains infrequent word components. Due to its abstract, scientific nature, the term also lacks intuitive meaningfulness for lay populations and may therefore be difficult to remember. While ‘antimicrobial resistance’ can be considered less stigmatizing than previous disease names such as ‘Wuhan novel coronavirus’ or ‘GRID’, the current terminology fails to signal the existential threat associated with the phenomenon and may lead lay audiences to underestimate its risks. Finally, given the inaccurate use of the umbrella term ‘antimicrobial resistance’ to describe the more specific phenomena of ‘antibiotic resistance’ or ‘antifungal resistance’, the term also has limited specificity. The frequently used acronym ‘AMR’ may be even more problematic; the three letter abbreviation is highly ambiguous because it can also refer to ‘anisotropic magnetoresistance’, ‘automatic meter reading’ or an Arabic male name, to list but a few.Following on from the above analysis, it appears that the communication of AMR is challenged by the psycholinguistic properties of its name. Drawing on previous research findings, the consequences might be far-reaching, for example influencing the attention paid to the health threat and even the feelings of truth or risk associated with relevant media communications.While previous scholars have called for a rebranding of AMR, for example suggesting to build consensus around the consistent use of one existing term (e.g. drug resistance),Based on the review above, I propose three recommendations for the overdue renaming process of AMR: (i) reduce variability of the names of AMR to one term that is universally used and understood; (ii) choose a term that is (a) short and easy to pronounce, (b) intuitively meaningful to lay audiences and indicative of the existential threat linked to AMR and (c) uniquely associated with the topic of AMR; and (iii) ensure that the name translates unambiguously across different languages and cultures.The rebranding of a global health threat like AMR requires a large-scale, unified campaign led by an interdisciplinary team of psychologists and clinicians and spearheaded by an international organization such as the WHO. In addition to the specific AMR name changes suggested above, a wider evaluation and revision of all related terminology such as ‘antimicrobial stewardship’ is likely to be necessary. The success of such language change will undoubtedly determine the international response to AMR over many years to come.This work was supported by a Leicester-Wellcome Trust ISSF Fellowship (reference 204801/Z/16/Z).None to declare.


Oxidative stress is defined as “an imbalance between oxidants and antioxidants in favor of the oxidants, leading to a disruption of redox signaling and control and/or molecular damage”. This Commentary presents basic features of this global concept which has attracted interest in biology and medicine. The term “antioxidants” in cellular defense against oxidants predominantly includes antioxidant enzymes with their substrates and coenzymes. Exogenous low-molecular-mass compounds also have a role, but this is more limited. Multiple biomarkers of damage due to oxidative stress have been identified for different molecular classes , and the current state of practical aspects in health and disease is delineated. Since its introduction in 1985 , and it A brief survey of the literature in the Web of Science gives over 450,000 hits for the term “oxidative stress”, with about 40,000 new additions in 2020. Unsurprisingly, a comprehensive view on the current development of this term would be challenging.The global concept of “Oxidative Stress” is defined as “an imbalance between oxidants and antioxidants in favor of the oxidants, leading to a disruption of redox signaling and control and/or molecular damage” ,5. It haThe molecular mechanisms of metabolic regulation include a multitude of chemical means. Structure and functions are implemented by orchestrated chemical modification of proteins, lipids, carbohydrates, and, not-the-least, nucleic acids. Redox reactions contribute to regulation, and it is noteworthy that there is crosstalk between different modes of regulation, e.g., between redox modifications and phosphorylation/dephosphorylation of proteins. Chemically reactive molecules of low-molecular-mass (“reactive species”) have been extensively investigated in their role in regulation. Recent accounts were given for reactive oxygen species (ROS) , reactivOn the other side of the redox balance, the defense against damaging levels of oxidants consists of several types of antioxidant enzymes in conjunction with their back-up systems, as well as of low-molecular-mass antioxidants, forming an antioxidant network . The comIn their textbook, Halliwell and Gutteridge devoted a chapter to antioxidants synthesized in vivo  . Due to the complexity of interlinked stress response systems, future research will focus on redox systems biology.


American Journal of Epidemiology. With the title “Invited Commentary: The Disillusionment of Developmental Origins of Health and Disease (DOHaD) Epidemiology” (We were surprised by the first article in the January issue of the miology” , we antimiology” . The comother than teratology (We do not understand how criticism of an article on a specific topic could justify a title indicative of disillusionment with the epidemiology of DOHaD in its entirety, especially as the DOHaD concept focuses on developmental exposures ratology . The aut


While information regarding this new class of signaling molecules in plants is scarce, the enzymes responsible for their synthesis have recently been elucidated. This review focuses on InsP6 synthesis and its conversion into PP-InsPs, containing seven and eight phosphate groups (InsP7 and InsP8). These steps involve two types of enzymes: the ITPKs that phosphorylate InsP6 to InsP7, and the PPIP5Ks that phosphorylate InsP7 to InsP8. This review also considers the potential roles of PP-InsPs in plant hormone and inorganic phosphate (Pi) signaling, along with an emerging role in bioenergetic homeostasis. PP-InsP synthesis and signaling are important for plant breeders to consider when developing strategies that reduce InsP6 in plants, as this will likely also reduce PP-InsPs. Thus, this review is primarily intended to bridge the gap between the basic science aspects of PP-InsP synthesis/signaling and breeding/engineering strategies to fortify foods by reducing InsP6.Inositol pyrophosphates (PP-InsPs) are an emerging class of “high-energy” intracellular signaling molecules, containing one or two diphosphate groups attached to an inositol ring, that are connected with phosphate sensing, jasmonate signaling, and inositol hexakisphosphate (InsP The IPMK enzyme is encoded by two genes in Arabidopsis, AtIPK2α and AtIPK2β P4 and to a final InsP5 product . Bo. Bo3 can product . 5-kinased InsP6  [30]. at6 biosynthesis is the phosphorylation of InsP5 to InsP6. This step is catalyzed by only one type of enzyme in nature, the inositol pentakisphosphate 2-kinase (IPK1), so named because all known IPK1 enzymes phosphorylate the 2-position of InsP5 . PH. PH6 andin vitro . InsP8 hormation . Togethe7 has a ~7-fold stronger binding affinity than InsP6 to OsSPX4, recent genetic analyses greatly support the idea that InsP8 is the major signaling molecule, or proxy, that conveys information on the Pi status within the plant cell [atipk1, atitpk1, atitpk4 and atvip1/vip2 mutants commonly show defects in Pi sensing, such that the PSR is turned on even when grown under Pi-replete conditions [8 levels  domain of TIR1, suggesting that InsP6 is a cofactor for the auxin receptor [We now know in greater detail that PP-InsPs likely function in binding to plant hormone receptors and transcription factor complexes involved in Pignaling . Auxin iignaling ,64. Auxiignaling ,66. The receptor .5 in the crystallized structure of a homologous plant hormone-JA co-receptor [5 binds to and stabilizes COI, suggesting that InsP5 is a cofactor for the JA receptor [5 and InsP6, suggesting that the PP-InsPs might be the true cofactor for the JA receptor [A later study identified InsPreceptor . JA is areceptor . Similarreceptor ,70,71. Jreceptor . Sheard receptor ,72. A streceptor . 6 in plants will also result in reduction in PP-InsPs. Most characterized Arabidopsis mutants showing alterations in InsP6 also have impacted the intracellular levels of InsP7 and InsP8 , the first committed step in inositol synthesis, have decreased InsP6 and are more susceptible to pathogenic viruses [Given the link between InsP insects . This imT plants . Additio viruses . While t6, such as Phytase, or to knock-down the expression of genes required for InsP6 synthesis. By doing so, the idea is that only specific tissues will have reduced InsP6. This strategy works well to reduce InsP6 in seeds, for example, without negatively impacting vegetative tissues. One potential drawback of this approach is that the reduction in InsP6 may also affect the precursor available for PP-InsP synthesis in these transgenic plants. It is also important to consider that plants store approximately 1% InsP7 and InsP8 in seeds [mrp5 InsP6 transporter mutants indicate that InsP6 modulation in seed can result in increases in PP-InsPs [Ultimately, understanding the genetic mechanisms for controlling PP-InsP synthesis and function is critical for developing novel low-phytate crops that are not compromised by changes in PP-InsP signaling. A recent review nicely details existing transgenic strategies used to reduce phytate in plants . A commoin seeds . We do n


Accordingly, their activity is regulated by complex mechanisms, notably by dopamine itself, via inhibitory D2-autoreceptors and the neuroprotective neuronal Ca2+ sensor NCS-1. Analyzing regulation of SN DA neuron activity-pattern is complicated by their high vulnerability. We studied this activity and its control by dopamine, NCS-1, and glucose with extracellular multi-electrode array (MEA) recordings from midbrain slices of juvenile and adult mice. Our tailored MEA- and spike sorting-protocols allowed high throughput and long recording times. According to individual dopamine-responses, we identified two distinct SN cell-types, in similar frequency: dopamine-inhibited and dopamine-excited neurons. Dopamine-excited neurons were either silent in the absence of dopamine, or they displayed pacemaker-activities, similar to that of dopamine-inhibited neurons. Inhibition of pacemaker-activity by dopamine is typical for SN DA neurons, and it can undergo prominent desensitization. We show for adult mice, that the number of SN DA neurons with desensitized dopamine-inhibition was increased (~60–100%) by a knockout of NCS-1, or by prevention of NCS-1 binding to D2-autoreceptors, while time-course and degrees of desensitization were not altered. The number of neurons with desensitized D2-responses was also higher (~65%) at high glucose-levels (25 mM), compared to lower glucose (2.5 mM), while again desensitization-kinetics were unaltered. However, spontaneous firing-rates were significantly higher at high glucose-levels (~20%). Moreover, transient glucose-deprivation (1 mM) induced a fast and fully-reversible pacemaker frequency reduction. To directly address and quantify glucose-sensing properties of SN DA neurons, we continuously monitored their electrical activity, while altering extracellular glucose concentrations stepwise from 0.5 mM up to 25 mM. SN DA neurons were excited by glucose, with EC50 values ranging from 0.35 to 2.3 mM. In conclusion, we identified a novel, common subtype of dopamine-excited SN neurons, and a complex, joint regulation of dopamine-inhibited neurons by dopamine and glucose, within the range of physiological brain glucose-levels.Dopaminergic (DA) midbrain neurons within the substantia nigra (SN) display an autonomous pacemaker activity that is crucial for dopamine release and voluntary movement control. Their progressive degeneration is a hallmark of Parkinson's disease. Their metabolically demanding activity-mode affects Ca Dopamine and dopamine-releasing (DA) neurons are important for a variety of brain functions and processes like movement control, habit-formation, conditioning, cognition, novelty-related behavior, motivation, reward prediction, and glucose homeostasis  during action potentials  feed-back and feed-forward mechanisms , and leading to hyperpolarized membrane potentials, but other signaling mechanisms are described   approaches to study neuronal activity in vital mouse brain slices. MEA recordings followed up by spike-sorting allowed us to analyze SN DA neurons without selection-bias and with much higher throughput compared to patch clamp techniques. Based on their dopamine-responses, we identified two types of SN neurons that were either dopamine-excited or dopamine-inhibited. Both SN populations were similar in size. The number of dopamine-inhibited SN DA neurons with desensitized responses was reduced by NCS-1 activity, and increased by elevated extracellular glucose, but the kinetics of inhibitory dopamine-responses were not altered. SN DA neurons displayed fast and reversible glucose-responsiveness in a dose-dependent manner, with higher electrical activity at elevated glucose levels, and within the physiological range of brain glucose levels. Thus, SN DA neurons display GE-neuron properties, similar as beta-cells.All mice were bred and housed in the facilities of the University of Ulm, according to the German Tierschutzgesetz and the directive 2010/63/EU. All animal procedures were approved by the Regierungspräsidium Tübingen (Reg. Nr. 0.147 and TV1043). Only male mice were analyzed. Wildtype mice are derived from C57BL/6J. NCS-1 KO mice (obtained by Olaf Pongs) were back-crossed at least 10 times into C57BL/6J , and perforated patch clamp recordings were performed and analyzed, as previously described , and stainless steel blades (Campden Instruments Ltd.). ACSF contained (in mM): 125 NaCl, 2.5 KCL, 25 NaHCO3, 1.25 NaH2PO4, 2 MgCl2, 2 CaCl2, and 25 glucose, bubbled with carbogen (95% CO2/5% O2) for pH adjustment (7.3) and oxygenation. Slices were allowed to recover for 30 min at room temperature in the same ACSF.For juvenile mice (~PN 13), after decapitation, the brain was quickly removed from the cranial cavity, cooled and cut into 250 μm coronal midbrain slices in ice cold artificial cerebrospinal fluid (ACSF) using a vibratome  for pH adjustment (7.3) and oxygenation. Slices were allowed to recover for 1 h at 37°C in ACSF-recovery solution containing (in mM): 125 NaCl, 2.5 KCl, 25 NaHCO3, 1.25 NH2PO4, 1 MgCl2, 1 CaCl2, 25 mM glucose.For adult mice, brain slice preparation was carried out utilizing a slightly altered version of the “slice it hot” protocol . We added 10 μM DNQX disodium salt (Tocris) and 10 μM Gabazine (Tocris) to block fast synaptic transmission. When glucose was below 25 mM, sucrose was added to get a total of 25 mM sugar in the solution to keep the osmolarity stable (300–315 mOsm/l). ACSF was bubbled with carbogen (95% CO2/5% O2) for pH adjustment (7.3) and oxygenation.The ACSF for MEA-recordings (“recording-ACSF”) contained (in mM): 125 NaCl, 2.5 KCl, 25 NaHCOFor MEA-recordings 3D-Biochips were used, manufactured by Qwane Biosciences SA (Switzerland). The electrode array layout of the MEA-chips was customized for covering the shape of the SN in coronal mouse brain sections. The MEA-chips contain 60 3D tip-shaped platinum electrodes, arranged in a 15 row × 4 column array. Interelectrode distance is 100 μm in rows and 90 μm in columns (measured from center to center). Each electrode is 30 μm in diameter, and the tip extends 25–40 μm from the base. The surface of the chips is covered by a 5 μm layer of SU-8 epoxy and has an electrical impedance of 500–800 kΩ. For optimized tissue to electrode contact, biochips were plasma cleaned every second week for 2 min under low vacuum . MEA chips were stored at 4°C, and reused for 3–6 months depending on the intensity of usage.MEA recordings were carried out using either a USB MEA1060-Up-BC System or a MEA2100-2x60 System . For the MEA1060-System, slices were mounted onto the MEA-chip under a stereoscope (Leica M165C). For the 2100 MEA System, slices were directly mounted on the amplifier with help of a video table . Slices were kept in place by a self-made grid, consisting of nylon strings affixed to a semi-circle platinum wire . Careful and correct positioning of the slice on the chip and placing the grid without moving or harming the slice was crucial for successful experiments. Before and after placing the grid, images were taken to document the MEA chip positioning .The recording chamber containing the MEA-chip was constantly perfused with the carbogenated recording-ACSF by a peristaltic pump . The temperature control of the inlet cannula  was set to 35°C and the inbuilt amplifier heating plate to 40°C, resulting in a bath temperature of 31–33°C (checked by a hand-thermometer before each experiment). After transfer into the recording chamber, slices were allowed to equilibrate in recording-ACSF for 30 min.Data were sampled at 20 kHz using the MC_Rack software . Data was recorded using a low pass  and a high pass (200 Hz) butterworth 2nd order filter. The software allows simultaneous recordings and online analysis. The so-called spike analyzer tool was used to identify the electrodes displaying activity directly during recordings: This tool is an in-built spike sorter that detects spikes within the signals, recorded by each electrode. The threshold for spike detection is set automatically by the software and individually for each electrode depending on the signal to noise ratio. Detected spikes were continuously displayed in the spike analyzer display. Electrodes showing a reaction to DA application  were marked for further data analysis (see below).The basic experimental design, carried out in recording-ACSF, was as follows (with 2.5 mM glucose if not stated otherwise): 10 min baseline recording of pacemaker-activities , followed by bath-application of 100 μM dopamine hydrochloride for 15 min, and a 20 min wash-out phase of dopamine. For DNIP (D2R/NCS-1 interaction prevention) experiments the DNIP peptide, or its scrambled (srDNIP) control, were synthesized by Genscript according to the published amino acid sequences  were already marked during the recording, based on the online analysis options in the MC_Rack software. To minimize file sizes, recording files were re-recorded containing only the electrodes displaying a response to dopamine (either increased or decreased event-rate). The generated second mcd file was imported into Spike2 and converted to a smrx file.Spike sorting of MEA recordings was carried out with Spike2 software . A threshold trigger was manually set by the experimenter, depending on the signal to noise ratio of the respective recording. The detected spikes displayed an amplitude of ~25-50 μV with a background noise of 15-25 μV. Via principal component analysis (PCA), Spike2 generates so-called spike templates, by matching and grouping spikes according to their principal components. These principal components are distinct features of the spikes like shape, amplitude, and length. The algorithm tries to separate the spikes in a direction of the largest variance. Meaning that the principal components with the highest variation in-between are chosen to generate the final spike templates. Spikes were separated by the software choosing the first two or three principal components Lewicki, . TemplatIf spike sorting by automatic Spike2 analysis was successful, the activity will be split into separate single unit activities. This means, that each activity, recorded from the individual electrodes, can be assigned to a single neuron. Since this was not always the case, after the automatic principal component analysis by Spike2 software, manual cluster analysis optimization by the experimenter is often necessary, to sort out appropriate SUAs out of automatically classified multi unit activity (MUA).For identification of a single unit activity (SUA), the sorted activity was manually checked in Spike2 for the following pre-selection criteria: (a) a lack of events occurring during the first 200 ms (short ISI range) shown in an interval histogram: the number of events before the first big peak of the interval histogram must not exceed 15% of this peak. (b) A clear and regular pacemaker activity, belonging to one unit, as judged by autocorrelation. The autocorrelation is defined as the correlation of the activity of a unit with a delayed copy of itself. (c) A lack of cross-correlation with other units recorded from the same electrode . (d) The appropriate typical shape of the waveform average of the unit. After Spike2 analysis, smrx files containing traces, including timepoints of each spike of potential SUAs, were imported into the Neuroexplorer software  to further analyze spontaneous activities of all recorded units for all electrodes. For this, autocorrelation as well as cross-correlation probability histograms were generated and analyzed. As before, autocorrelation histograms correlate a unit with a delayed copy of itself, while cross-correlation analysis allows to identify if the same SUA is recorded by more than one electrode, as all units recorded on one slice are analyzed for correlation. For both, 10 min of baseline activities were analyzed using a Boxcar filter smoothing routine of 3 bins (30 ms) in width  of each verified SUA was exported into excel from Spike2. To define the basal firing rate, the mean firing rate of a stable 10 min control period at the beginning of each recording was calculated. For describing pacemaker-regularity, the mean interspike-interval (ISI = 1/frequency) and its standard deviation (SD) were determined for this 10 min control period, to calculate the coefficient of variation (CV) of the ISI:For analysis of relative firing-rates in dopamine, firing-rates in the last minute in dopamine  were normalized to the mean firing rate during the 10 min control period. An inhibitory dopamine D2-AR response was classified as desensitized if the mean frequency in the last minute of dopamine was higher than 5% of the respective basal firing rate.50 values were determined by using the hill equation  vs. response-variable slope, according to Goutelle et al., 50 values are given as the mean of individual EC50, derived from individual fits for each analyzed cell , as well as from the fit of the mean values .Cumulative glucose dose-response curves were fitted and ECpost-hoc test) was used. For comparison of mean firing rates and CV-ISI in different glucose concentrations, repeated-measures one-way ANOVA tests were used (Friedman test with Dunn's multiple comparison post-hoc test). For comparison of mean firing rates, CV-ISI and relative activities at minute 15 of DA between NCS-1 KO/WT and DNIP/srDNIP as well as DA-excited and -inhibited SN neurons unpaired Kruskal-Wallis tests with Dunn's multiple comparison were used. To detect differences in the change of firing-rate and the CV-ISI between decrease and increase of glucose concentration the Wilcoxon matched-pairs signed rank test was used. A single asterisk (*) denotes a p < 0.05, two (**), three (***), and four asterisks (****) denoting p < 0.01, 0.001, and 0.0001, respectively. All statistical analysis and data transformations were performed in Prism .Data are given as mean ± standard error of mean (SEM) if not stated differently. Standard Error (SE) or Standard Deviation (SD) are given as indicated. The number of identified SUAs  is given by n, number of mice is given by N. Data were probed for normal distribution by using the Shapiro-Wilk normality test. As some datasets were not normally distributed, for most comparisons, non-parametric tests were used for probing for significant differences. For statistical comparisons of basal firing rate, CV-ISI and relative activities at minute 15 in dopamine, a two-tailed, unpaired, non-parametric Mann-Whitney-test (for pair-wise comparisons) was used. Differences in the ratios of sensitized to desensitized D2-AR responses were assessed by chi-square test for pair-wise group comparisons. To evaluate differences in firing rates over time, two-way repeated-measures ANOVA , similar as previously described . Neuroanatomical positioning in maps was based on a mouse brain atlas . The utilized MEA-chip (custom-build by Qwane Biosciences SA) contained 60 3D tip-shaped platinum electrodes (30 μm tips), arranged in a 15 row × 4 column array . Coronalin vitro in synaptic isolation a slow, very regular pacemaker-activity , and a well-described full inhibition of pacemaker-activity in response to extracellular dopamine , but only electrodes with identified single unit activity (SUA) were further analyzed. SUA and MUA were identified after spike-sorting and principal component analysis (PCA). Electrodes that did not respond to dopamine with altered event-rates were not further analyzed, but we analyzed all electrodes that displayed responses to dopamine (higher or lower event-rate). Interestingly, we detected a large population of SUAs that were excited by dopamine . We neven = 30 from 11 slices, N = 7 mice; adults: 42% of all dopamine-responsive cells; 3 cells/slice; n = 42 from 14 slices, N = 7 mice). In most recordings from juveniles , and in about 50% from adults (n = 22 of 42), these dopamine-excited SN cells showed no activity at all before dopamine application but got transiently excited by dopamine . The subpopulation of adult dopamine-excited cells that did display pacemaker activity before dopamine-application  increased its frequency almost 3-fold during dopamine application to 8.8 ± 6.7 Hz (mean ± SD). Pacemaker frequencies in dopamine were significantly higher in neurons that displayed activity before dopamine-application compared to those without activity (about 50%). The baseline pacemaker-activity of dopamine-excited cells compared to that of dopamine-inhibited cells appeared a bit faster but was not significantly different. However, the pacemaker (before dopamine) was less precise in adults . We also mapped the anatomical location of dopamine-excited and dopamine-inhibited cells  glucose-concentrations for individual SN DA, we fitted dose-response curves for each individual neuron, as well as the mean values at each concentration of all analyzed neurons . Both approaches resulted in similar EC50 values, slightly below 1 mM glucose . Thus, we separated the analyzed cells into two groups  and fitted them separately. Indeed, the dose-response curves were better fitted by these two fits, than by one over-all fit and resulted in EC50 values of 2.23 mM (n = 8) and 0.35 mM (n = 5) glucose (The transient glucose-deprivation experiments demonstrated for SN DA neurons glucose-sensing properties of the GE-type. To further quantify glucose sensitivity within the (patho-) physiological range of brain glucose levels, we carried out MEA experiments where glucose concentrations were stepwise elevated from 0.5 mM up to 25 mM to determine dose-response curves and EC glucose , indicat50 values separately, for sensitized and desensitized neurons, leading to EC50 values of 0.35 ± 0.05 mM (n = 3) and 0.85 ± 0.17 mM  range of brain glucose-levels, another one in the hypoglycemic range (<0.7 mM)  and broad action potentials (>2 ms) , could also be involved in mediating desensitization of inhibitory dopamine responses in SN DA neurons, possibly in interplay with D2-receptors and other conductances, as already described  physiological range of brain glucose levels. Individual dose-response curves indicate that SN DA neurons might display different glucose sensitivities, with one population displaying EC50 values in the euglycemic range (EC50: ~2.0 mM) and another one within hypoglycaemic (EC50: ~0.35 mM) brain glucose levels. These values correspond well with those described for GE neurons in the lateral hypothalamus, with an EC50 of ~0.8 mM glucose  have been described , hexokinases/glucokinase (GK) for intracellular glucose phosphorylation, and a variety of downstream ion channels and receptors (reviewed e.g., in Routh et al., + channels, as described for pathophysiological reduction of SN DA activity in response to PD stressors (Liss et al., Future studies will address the molecular mechanisms of glucose sensing in SN DA neurons. Our first experiments indicate a complex mechanism that is not simply explained by activation of K-ATP channels or A-type KThe original contributions presented in the study are included in the article/The animal study was reviewed and approved by the Regierungspräsidium, Referat 35, Konrad Adenauer Strasse 20, 72072 Tübingen.NM and KK performed MEA experiments and data analysis. CP carried out perforated patch clamp experiments. NM and KK performed immunohistology. MF and AD carried out initial MEA pilot-experiments. BL designed the study and data analysis. BL and NM wrote the manuscript. All authors revised the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The primary outcome was the closure rate of hsPDA after the first treatment course with paracetamol or ibuprofen. Secondary outcomes included the constriction rate of hsPDA, the re-opening rate, and the need for surgical closure. Fifty-two and 49 infants received paracetamol or ibuprofen, respectively. Paracetamol was less effective in closing hsPDA than ibuprofen , but the constriction rate of the ductus was similar , as confirmed by logistic regression analysis. The re-opening rate, the need for surgical closure, and the occurrence of adverse effects were also similar.Our aim was to assess the efficacy and safety of intravenous (i.v.) paracetamol vs. i.v. ibuprofen for the treatment of hemodynamically significant patent ductus arteriosus (hsPDA) in preterm infants. This is a multicenter randomized controlled study. Infants with a gestational age of 25Conclusions: Intravenous paracetamol was less effective in closing hsPDA than ibuprofen, but due to a similar constriction effect, its use was associated with the same hsPDA outcome. These results can support the use of i.v. paracetamol as a first-choice drug for the treatment of hsPDA.Trial registration:Clinicaltrials.gov: NCT02422966, Date of registration: 04/09/2015; EudraCT no: 2013-003883-30.The online version of this article (10.1007/s00431-020-03780-8) contains supplementary material, which is available to authorized users. Patent ductus arteriosus (PDA) is a frequent complication in preterm infants with respiratory distress syndrome (RDS), and 60–70% of preterm infants of < 28-week gestation receive medical and/or surgical treatment for PDA . The proThe current treatment of PDA encompasses two steps: the first is the pharmacological treatment with a NSAID; the second, in case of medical treatment failure, is the surgical ligation, which should be avoided, if possible, due to the associated severe complications . StandarSuccessful closure of PDA with oral paracetamol has been reported by RCTs in several preterm infants –14. MoreOn this basis, we deemed a further study necessary to confirm or confute previous findings on the efficacy of i.v. paracetamol and to learn more about its possible side effects. Thus, the present study assessed the efficacy and safety of i.v. paracetamol in comparison with i.v. ibuprofen for the treatment of hsPDA in preterm infants.Clinicaltrials.gov: NCT02422966; EudraCT no: 2013-003883-30) involving five Neonatal Intensive Care Units in Italy. The study was approved by institutional review board and relevant authorities according to local regulations.This is a multicenter randomized controlled study  > 2 times the upper boundary of the normal range  [Inclusion criteria were gestational age of 25tive PDA , 21. Exc140 U/L) .Infants were randomly assigned in blocks to a treatment group in 1:1 ratio. Patients in group I received 15 mg/kg/6 h of i.v. paracetamol  for 3 days –14. Pati+0–27+6 weeks or 28+0–31+6 weeks.The allocation sequences consist of computer-generated random numbers. Since the frequency of the PDA is inversely related to the gestational age, the inclusion of patients was balanced in each treatment group according to the following gestational ages: 252 50–60 mmHg, PaCO2 < 65 mmHg, pH > 7.20, and SpO2 90–95%.Daily clinical care of enrolled patients was performed by attending physicians in accordance with the common practice at each center. Daily fluid intake was started with 70–80 mL/kg and gradually increased by 10–20 mL/kg/day on the basis of changes in body weight, serum sodium concentrations, and osmolality, with a target intake of 150–160 mL/kg at the end of the first week of life. In case of systemic hypotension refractory to fluid replacement therapy, dopamine and/or dobutamine treatment were provided. For the treatment of RDS, infants received oxygen therapy, respiratory support, and rescue surfactant treatment in order to achieve the following targets: PaOEchocardiography was repeated every 24 h during the first treatment course, 24 h after the last dose of the treatment, at follow-up visits, and in case of clinical suspected PDA re-opening. Cardiac ultrasound was performed by expert personnel, specifically a pediatric cardiologist or a neonatologist who has achieved adequate expertise in newborn heart ultrasound, who were blinded to the study and treatment groups. More persons performed cardiac ultrasounds in each participating centers. Further details about respiratory management and timing for routine blood analysis were previously reported .The primary outcome of the study was the closure of hsPDA after the first course of treatment with paracetamol in comparison with ibuprofen.Secondary outcomes were the constriction of hsPDA after the first course of treatment with paracetamol in comparison with ibuprofen (constricted DA was defined as closed DA or not hsPDA), the closure of hsPDA and the constriction rate after the second course of treatment with ibuprofen, and the re-opening rate and the incidence of need for surgical closure 30 days after the enrollment.Laboratory tests were performed at patients’ screening, at the end of first and second course of treatment, and during the follow-up visits at 7 and 30 (± 2) days after the enrollment. Clinical laboratory tests included a count of red blood cells, white blood cells, and platelets, serum value measurement of hemoglobin/hematocrit, creatinine, urea nitrogen, total bilirubin, total proteins, liver enzymes, sodium, potassium, and calcium. For study purposes, renal failure was defined as serum creatinine concentration > 1.5 mg/dL and urine output < 1 mL/kg/h during a 24-h collection period. Liver failure was defined as elevated liver enzymes more than two times the upper boundary of the normal range  . Necroti2 and mean airway pressure values, need for non-invasive , biphasic positive airway pressure (BiPAP), nasal intermittent mandatory ventilation (N-IMV), humidified high flow nasal cannula (HHFNC)) and invasive respiratory support (patient triggered ventilation (PTV), including synchronized intermittent positive pressure ventilation (SIPPV), synchronized intermittent mandatory ventilation (SIMV), pressure support ventilation (PSV) or high frequency oscillatory ventilation (HFOV)), need for surfactant treatment, and adverse events. We also reported the occurrence of sepsis, IVH, periventricular leukomalacia (PVL), BPD, retinopathy of prematurity (ROP), NEC, length of hospital stay, and mortality.The following data were recorded for each infant: gestational age, birth weight, gender, mode of delivery, Apgar score at 5 min, main maternal pathologies, antenatal steroid treatment, and vital signs, such as heart rate, systolic, diastolic, and mean arterial blood pressure at the start of treatment, peak FiODiagnosis of sepsis was based on clinical and laboratory data  and confirmed by positive blood cultures . IVH wasAll study data were collected on a web-based electronic case report form, specifically designed for this study.Assuming a 25% ibuprofen failure rate in closing hsPDA  and a 5%The following populations were defined for statistical analysis: the modified intention-to-treat (m-ITT) population as all randomized patients completing the first treatment course, having baseline and day 3 echocardiographic assessment, the per protocol (PP) population as patients from the m-ITT population with no major protocol violations, and the safety population (SP) as all patients who took at least one dose of study medication.Analysis of the primary and secondary end points of the study was carried out on the m-ITT and PP populations, while safety and tolerability assessments were carried out on the SP population.t” test or by Wilcoxon rank sum test in case of deviation from normality assumptions. Categorical variables were compared using the χ2 test or Fisher’s exact test. P < 0.05 was considered statistically significant.Clinical characteristics of infants in the paracetamol and ibuprofen groups were described using mean value and standard deviation, median value and interquartile range (IQR), or frequencies and percentage. Normality of data distribution was assessed by Shapiro–Wilk’s test. Parametric continuous variables were analyzed by the Student’s “2 > 0.25 vs. ≤ 0.25 on the closure of PDA. These variables were selected because there were no differences between study groups at univariate analysis, but gestational age and the peak of FiO2 have been previously found to be correlated with the risk of developing hsPDA [A multiple logistic regression analysis was performed using backward variable selection to assess the potential independent effect of the first course of paracetamol vs. ibuprofen, 25–27 vs. 28–31 weeks of gestational age, and peak FiOng hsPDA . The gooThe study was carried out from December 2015 to January 2019. Figure P = 0.877) of life in the paracetamol and ibuprofen group, respectively , but the success rate in constricting the DA was similar . The effectiveness of the second course of treatment with ibuprofen was also similar in infants who had been previously treated with paracetamol or ibuprofen, either in closing  and in constricting hsPDA   Table .Table 3PP = 0.078) in infants both in the paracetamol and ibuprofen groups, as the need for surgical closure   but did not affect the likelihood of PDA constriction . Patients’ gestational age and peak FiOOccurrence of adverse events was similar in paracetamol and ibuprofen groups and is detailed in Supplemental Table n = 2, in the paracetamol group) or intestinal volvulus .Four infants died for NEC (n = 300): both studies used the same course of paracetamol and ibuprofen, at the same post-natal age, with the only relevant difference being that they enrolled more immature infants than our study. However, other studies are in agreement with our results: Roofthooft and Alan reported case series in which i.v. paracetamol failed to close hsPDA [n = 842) reported that the use of paracetamol as first-treatment course increased the risk of hsPDA closure failure in comparison with ibuprofen both in infants born at 23–24 and 25–28 weeks of gestation [In this study, we assessed the efficacy of i.v. paracetamol in comparison with i.v. ibuprofen for the treatment of hsPDA in preterm infants and we found that paracetamol was less effective in closing hsPDA than ibuprofen. Our result disagrees with previous findings by Dang  and Oncese hsPDA , 34, andestation . Moreoveestation .It is relevant that the success rate in constricting hsPDA (defined as closed DA or not hsPDA) was similar in infants treated with paracetamol or ibuprofen (81 vs. 90%). This result is in discordance with the study by Liebowitz et al. who found that paracetamol has a lower hsPDA constriction effect than ibuprofen and indomethacin . HoweverWe observed that a second pharmacological course with ibuprofen was effective in closing hsPDA refractory to the first treatment course in the preterm infant. This result is in agreement with previous studies which demonstrated that repeated courses of ibuprofen are an effective and safe alternative for surgical closure and should be considered after failure of the first course of ibuprofen , 37.We found that infants born at 25–27 weeks of gestational age had lower likelihood of PDA constriction than infants born at 28–32 weeks of gestational age. These results confirm previous findings that hsPDA occurrence is inversely related to gestational age probably due to the increase of DA reactivity to oxygen and decrease of circulating vasodilator concentration occurring as gestational age progresses . MoreoveIn our study, we also collected data regarding adverse effects of drugs, the occurrence of which was similar for paracetamol and ibuprofen. Both were substantially safe, but the size of our population did not allow firm conclusions on this issue.2 and pO2 during treatment and, therefore, we could not evaluate the effect of oxygen therapy on PDA closure.A limitation of the study was the lack of a double-blind design due to the different number of daily doses of paracetamol and ibuprofen. However, the primary end point (closure of hsPDA) was evaluated through objective echocardiographic cardiovascular measurements and we are confident that this could contribute to limit the risk of bias. Another limitation is that our echocardiographic criteria for hsPDA diagnosis , although they are widely diffused, may have significant variability between observers. Moreover, we could not evaluate the effect of hsPDA closure or constriction on patients’ main outcomes, such as mortality and BPD, due to the lack of a control group using a non-interventional conservative management of PDA. However, these outcomes were not the objectives of our study. We recognize that our study has a relative lack of novelty compared with other studies; however, we believe it may be very useful for future meta-analyses. We did not collect serial data on FiOWe found that the first course of treatment of hsPDA with i.v. paracetamol was less effective than i.v. ibuprofen in closing hsPDA in preterm infants with gestational age ≥ 25 weeks but has a similar constriction effect and its use was associated with the same hsPDA outcome, i.e., the same need for a second course of treatment, re-opening rate, and surgical closure requirement. Both drugs had similar safety profile. These results can support the use of i.v. paracetamol as a first-choice drug for the treatment of hsPDA.ESM 1(DOCX 28 kb)ESM 2(DOCX 29 kb)ESM 3(DOCX 46 kb)ESM 4(DOC 352 kb)ESM 5(DOC 49 kb)


The open rich-client Molecule Set Comparator (MSC) application enables a versatile and fast comparison of large molecule sets with a unique inter-set molecule-to-molecule mapping obtained e.g. by molecular-recognition-oriented machine learning approaches. The molecule-to-molecule comparison is based on chemical descriptors obtained with the Chemistry Development Kit (CDK), such as Tanimoto similarities, atom/bond/ring counts or physicochemical properties like logP. The results are summarized and presented graphically by interactive histogram charts that can be examined in detail and exported in publication quality. The comparison of molecules lies at the heart of cheminformatics from its beginnings with molecular comparative studies addressing a wide range of research activities . A varieBesides the frequent use cases, which are already covered by available solutions, current machine learning tasks make demands on dedicated molecule-to-molecule comparisons, which have to be addressed by new specific applications to effectively support corresponding research activities.“Intelligent” molecular recognition systems based on new deep learning approaches in cheminformatics try to predict a molecule in question (the system’s output) from a specific molecular representation (the system’s input), where the input representation of the desired molecule may be a set of its molecular features, a pixel image of the molecule’s 2D structure or any other encoding that relates to the original molecule. To assess the predictive power of a molecular recognition system, the predicted molecules have to be comprehensively compared with their corresponding original molecules that were used to create the molecular representation for the system’s input. For these comparisons a fingerprint based Tanimoto similarity between original and predicted molecule may be used or the difference of their atom/ring counts may be calculated. Also differences regarding their physico-chemical properties like logP may be of interest. For large sets of original and corresponding predicted molecules these similarity or difference values may be neatly summarized by frequency histograms which then allow for a versatile and fast assessment of the recognition abilities of the machine with regard to the selected comparator. The new Molecule Set Comparator (MSC) application focuses on these comparisons and aims to alleviate them.MSC is a Java rich-client end-user application which architecturally follows a Model-View-Controller (MVC) pattern  and utilFigure The available descriptors for original/predicted molecule comparison are summarized in Table The MSC input view allows the concurrent selection of multiple descriptors for original/predicted molecule comparisons. A comparative histogram chart is then generated for each selected descriptor see Fig. : each hiSummarize button . Using more than 8 threads still yields improvement up to 16 threads (factor of 11.9 on the same machine). On average, a (basic CDK fingerprint) Tanimoto similarity comparison of one million original/predicted molecule pairs using 8 calculation threads and 16 gigabytes of RAM takes less than 3 min.MSC supports concurrent calculations via the The MSC GitHub repository contains the complete source code, all used libraries, installation instructions for all major platforms, a Gradle project for Netbeans as well as supplementary tutorials for installation, overview and application.MSC is a versatile and fast end-user tool for comparing large molecule sets containing millions of chemical structures. As a rich client it does not require any programming skills and runs on all major platforms . A major application area is the support of molecular-recognition oriented machine learning tasks that require a large-scale and thorough comparative analysis of molecular features: The MSC tool allows to replace tedious scripting approaches with cumbersome manual PDF views by fast, flexible and comprehensive graphical point-and-click inspections. In addition to saving time, the new open tool may provide insights that might have been overlooked otherwise.Project name: MSC.https://github.com/zielesny/MSC. Project home page: MSC repository at Operating system(s): Platform independent.Programming language: Java.Other requirements: JavaFX 14 , CDK 2.3License: GNU General Public License version 3.