The objective of this work is to design a molecular generator capable of exploring known as well as unfamiliar areas of the chemical space. Our method must be flexible to adapt to very different problems. Therefore, it has to be able to work with or without the influence of prior data and knowledge. Moreover, regardless of the success, it should be as interpretable as possible to allow for diagnosis and improvement. We propose here a new open source generation method using an evolutionary algorithm to sequentially build molecular graphs. It is independent of starting data and can generate totally unseen compounds. To be able to search a large part of the chemical space, we define an original set of 7 generic mutations close to the atomic level. Our method achieves excellent performances and even records on the QED, penalised logP, SAscore, CLscore as well as the set of goal-directed functions defined in GuacaMol. To demonstrate its flexibility, we tackle a very different objective issued from the organic molecular materials domain. We show that EvoMol can generate sets of optimised molecules having high energy HOMO or low energy LUMO, starting only from methane. We can also set constraints on a synthesizability score and structural features. Finally, the interpretability of EvoMol allows for the visualisation of its exploration process as a chemically relevant tree.  One of the main objectives of chemical research is to find a molecule that has desired properties for a given application. However, the molecular space being immeasurable, one needs to define strategies to efficiently explore its relevant parts. Even an incomplete enumeration of the chemical space limited to 17 heavy atoms  already leads to more than 160 billion compounds , 3.In the 1990–2000s, evolutionary algorithms were already used for de novo molecular generation . To limi et al. proposed a transfer learning approach to take advantage of the abundant data in pharmaceutical-type molecules and generate chemically feasible solutions for materials [In fact, several deep learning architectures were then published for de novo molecular generation. Among them, autoencoders are trained to convert points of their latent space to SMILES , 9–11 oraterials . Other naterials  or molecaterials . We shouaterials . All theAuthors have therefore suggested to use reinforcement learning to push those boundaries and orient the search towards desired properties. GAN can be associated with reinforcement learning to optimise properties, while using their discriminator to evaluate the likeliness of the solutions , 18. ThiThere is renewed interest with recent evolutionary methods leading to competitive results –28. ThisThe objective of our work is to design a molecular generator capable of exploring known as well as unfamiliar areas of the chemical space. Between drug-like generation and organic materials, the chemical space of interest is different . The molIn this paper, we present EvoMol, a new generic and simple molecular generation method using an evolutionary algorithm to sequentially build molecular graphs. To be able to search a large part of the chemical space, we define an original set of 7 local and chemically meaningful mutations.We calibrate our methodology using several properties of the literature that are classic and fast to compute. In this way we can also compare ourselves with state of the art methods. Targets are the QED , penalisTo demonstrate the flexibility of EvoMol, we tackle a very different objective issued from the organic molecular materials domain. Usually in this domain, the aim is to find a molecule with given electronic properties. It can be for example a desired HOMO or LUMO level or an UV-visible absorption / emission range. Such properties require quantum chemistry calculations to be precisely assessed. The objective function cost is therefore huge and increases rapidly with the molecular size.We show that our method achieves excellent performances on the optimisation of these electronic properties. We demonstrate that starting from methane, which has one of the lowest HOMO and highest LUMO in energies, our algorithm can generate sets of optimised molecules i.e. having high HOMO or low LUMO energies. We can also set constraints on a synthesizability score and structural features. Finally, we propose a chemically relevant visualisation tree to follow the exploration process.Beyond the question of the method, the representation of the solutions plays a crucial role for molecular properties optimisation. Ideally, the representation should allow for the definition of a rich, interpretable and valid neighbourhood while requiring small computational cost. In practice, such molecular representation does not exist, and a trade-off must be found.Early methods mainly represent the molecules as SMILES , a lineaThe other common representation is the molecular graph. It can be extracted from the latent space of deep learning methods , 13, 22.The behaviour of EvoMol is described in Algorithm 1. At first, the chemical subspace to explore is defined through the choice of the mutations on the molecular graph, the set of atoms, the molecular size limit and the filter rules. Then, the population is initialised with one or more molecules up to the maximum population size. The choice of the initial population is an often underestimated but crucial element of the knowledge available to the model. It can have a huge impact on the final performance of the model. The knowledge introduced in the form of an initial population can compensate ill-defined objective functions for very specific and complex tasks , single, double and triple. With these three actions, it is possible to reach a large portion of the molecular space. However, it require multiple steps to perform changes which could be considered as chemically rudimentary.Among the actions on molecular graphs that we define and present in Fig. Substitute atom type changes the type of an atom of the graph. Insert carbon corresponds to the insertion of a carbon atom between two existing atoms sharing a bond. The initial bond between the two atoms is removed and the carbon atom is linked to them with two single bonds. Only carbon can be inserted, as it is the backbone of organic chemistry and in order to limit the action space size. Cut atom removes an atom sharing exactly two bonds with two atoms not sharing a bond with each other. The two remaining atoms are then linked with a single bond. Finally, Move group relocates a functional group to a different atom of the molecular graph, while conserving the type of the removed bond. Functional groups are subgraphs only linked to the rest of the molecule by a single edge . Fig. We therefore define a set of secondary actions, using sequences of primary actions to create small shortcuts in the chemical space in order to accelerate the exploration. It should be noted that these actions do not extend the accessible chemical space. a priori filters discarding actions leading to invalid molecular graphs, without a need to apply the actions to assess the validity. The first filter prevents the dislocation of the molecular graph by prohibiting the use of actions leading to the formation of additional connected components. The second filter prevents the use of actions leading to incorrect valences. Since hydrogens are considered implicitly, only hypervalence leads to inconsistency. However, the implicitness of hydrogens complexifies the processing of charged atoms with our method. We do not define any action leading to their creation nor neutralisation, but we accept ions and zwitterions as input graphs by filtering the actions having an effect on the bonds of charged atoms, except for atom removal. Therefore, ionic subgraphs can be conserved or removed while actions are modifying the molecular graph.The successive application of our defined actions can be followed in an exploration tree. We will see that this approach allows relevant and interpretable figures. So, we ruled out recombination operations between solutions, which would result in less readable visualisations. We do not design any specific action to handle aromaticity, which is considered implicitly through the Kekulé forms that can be created. To guarantee the validity of the generated molecules, we define two Substitute atom type and cut atom can only be applied on a mutable atom. Change bond, insert carbon and move group can only be applied on a couple of atoms containing at least one mutable atom. This approach is illustrated by an example where we consider an optimisation of HOMO and LUMO energy levels for furane derivatives  corresponds to the octanol-water partition coefficient penalised by the SAscore and the presence of a large ring [‡ the normalised version. We have adapted the implementations of You et al. and Zhou et al. respectively [As stated in the introduction, we assess our method using several properties commonly used as objective functions. QED is a metric evaluating the drug-likeness based on the similarity of the distributions of a set of properties with known drugs . SAscorerge ring . In the rge ring , but it rge ring . Likewisectively , 24. We ectively . It is aectively . To defiectively .The previous metrics, especially plogP and QED, have been widely used to compare the molecular generation methods. However, they are optimised using different search space definitions in terms of available atom types and maximum sizes of molecules. This can have a huge effect on the results, particularly for plogP. In this article, we only compare EvoMol with methods using a similar space search definition.Because the optimisation of the previous properties can be trivial and in order to homogenise the evaluation of the methods, a benchmark named GuacaMol has been recently proposed . We evalAs a proof of concept in the domain of organic molecular materials, we also use our method to optimise two electronic properties, the HOMO and LUMO energy levels. Contrary to the previously presented benchmarks that depends on fast evaluations of fitness functions, HOMO and LUMO energies depend on quantum mechanics calculations with a heavy computational cost. Here, geometric optimisations are carried out with the Gaussian09 program and default parameters . The B3LFor all these objective functions, different initial conditions and parameters define our algorithm. We test the impact of the population size, its initial state, the atomic types set and the actions set. For QED, plogP, SAscore and CLscore populations sizes ranging from 1 to 457k are tested. For GuacaMol and electronic properties, we use either a relevant starting population (a ChEMBL subset or a furane core) or a simple methane molecule to assess the initial knowledge impact and to perform a demonstration in challenging conditions.‡ and CLscore. To provide a baseline, we run our algorithm to maximise each of these properties with a population size of 1, starting with the methane. This corresponds to a simple hill-climber algorithm with a first improver policy, as a unique solution is mutated until an improver is found. It means that a direct pathway must be found in the molecular space between the methane starting point and a molecule solution.The first case consists in optimising the set of fast metrics containing QED, both plogP versions, SAscoreWe conduct our space exploration on molecules containing C, N, O, F, P, S, Cl or Br atoms. For a fair comparison with other methods, we limit the sizes of the molecules to 38 heavy atoms. As the plogP is sensitive to the set of atoms, we perform a second run for its optimisation using only C, N, O or F atoms. The mutation is defined as the application of up to 2 successive actions, and the algorithm is ran for 1500 steps, with up to 50 tries to find an improver at each mutation. All experiments are ran 10 times and results are averaged.The results of the single individual optimisation . On the one hand, no method seems to find the best solutions on these benchmarks, resulting in high variability between the methods  is difficult. Furthermore, the choice of fingerprints and Tanimoto distances does not correspond to a chemical neighbourhood as defined by the actions on the molecular graph. Even more problematic, it does not seem possible to us to define chemically interpretable actions to make our neighbourhood correspond to the distances between fingerprints. Therefore, it is not a good objective function to guide our method towards improving solutions.With atom centred actions, EvoMol is a quite unconstrained molecule generator. The chemical soundness of the solutions has to be verified. In GuacaMol, a compound quality measurement is provided. 77% of the GuacaMol initial dataset pass this test. In this test evolutionary algorithms do not perform as well as RNN methods. For our method , 34% pass the quality check, quite similarly to comparable methods . HoweverSince EvoMol is designed to be flexible, we can implement an obligation to pass this filter in the generation process thus ensuring 100% validity of the solutions across all the research path. With this very conservative constraint, the mean score obtained on ten executions is 0.897. Among twenty, this task is the only one evaluating the ability of generators to propose molecules far from what is already known. EvoMol is able to handle both the multi-objective optimisation problem and validity constraints to deliver high performance. For the Osimertinib objective, the ratio of solution passing the quality measurement test range from 0% to 70%. Applying the filtering during the generation process allow us to reach a mean score of 0.959 with 100% validity and therefore without impacting performance. We have applied this methodology for a full run on all GuacaMol benchmarks. This constraint, the obligation to pass this quality filter is, as expected, not enough to ensure a chemical feasibility. Top scores for the MPO with and without the quality filter are depicted in Additional file Thanks to the different runs of our models, it is possible for once to appreciate the variability of these objectives as shown in the following Fig. In the end, with our different executions, we can observe a variability between the different runs easily of the order of 0.05 for the most complex metrics. We can therefore estimate that a difference on the total score of the order of 0.2 is not significant. Thus it is likely that EvoMol, GraphGA, CREM and MSO are in fact comparable in terms of pure optimisation performance on this set of benchmarks.The last case consists in optimising an electronic property. The frontier molecular orbital levels are key points for any reactivity problems, electroactive molecules and electronic or photonic organic materials. So, we choose to focus on the HOMO and LUMO energies. The energy levels are obtained with a geometric optimisation calculation in DFT.In a previous article we studied the QM9 and PC9 datasets that together encompass more than 200k different molecular calculations with up to 9 heavy atoms of C, N, O and F types . InitialOne could hope for a fast evaluation of quantum mechanics properties thanks to machine learning predictions to limit the cost of computation. However, we have demonstrated that the currently available datasets of molecular quantum chemistry results, like QM9 and PC9, are not diverse enough to train a general predictor . It is cThe data for methane are highlighted in Fig. Figure Our first attempt with EvoMol . The CLscore filter allows for greater diversity but has less impact on the solutions. Indeed in QM9 and PC9 (line D), the compounds with the highest HOMO energies are also amine derivatives (more often aromatic). Ultimately, we can notice that our method allows us to get close to the best energies in HOMO and LUMO starting from a worst case scenario.To be more realistic, we end up with an experiment that adds a structural constraint. We impose a furane core which is an aromatic ring resembling the conjugated systems used in organic materials. The research space is therefore more limited with 4 more heavy atoms to generate. Both HOMO and LUMO are also optimised with the CLscore sigmoid. Thanks to our approach with mutations acting near the atom level, we can propose an interesting visualisation of the exploration process for this experiment. In Fig. In the upper part of the figure, we can see that for the HOMO EvoMol tries alkyl, fluorine, alcohol and amine substitutions. We also notice that the operation of moving a substituent allows it to probe the interest of the different positions and their combinations. From there, an intensification takes place around the poly amine improvers. In the lower part, for the LUMO objective, the amine and alcohol are also probed but rapidly discarded. The first effective branch is associated with fluorine substitution, which then becomes more complex. It is worth noting the appearance of cyano and especially peroxo and oxygen fluoride functions which allow very good values for realistic solutions.These exploration trees mimic the way of working of a human chemist who, around efficient fragments, walks through the chemical neighbourhood in elementary steps. By this Fig. In this article, we present EvoMol, an efficient evolutionary algorithm for molecular generation. By design, it generates only valid molecular graphs and unique solutions. EvoMol can be used with a maximum population size of one molecule. In optimisation, this corresponds to a very naive approach called the hill-climbing algorithm. This simple climber finds a direct pathway to very good solutions for classical objective functions . Therefore, it showcases the limitations of such objectives as benchmarks. EvoMol can also generate large datasets of high scoring solutions, by intensifying thoroughly on promising areas of the chemical space.We show in this article that EvoMol is highly configurable and provides state of the art performances for both classical drug design  and molecular material problems. Contrary to many methods, EvoMol does not require prior knowledge extracted from a dataset to obtain high scoring solutions. It can therefore tackle very different problems and explore different chemical subspaces depending on the objective. We demonstrate that in EvoMol, bias can be strictly controlled. Prior knowledge can be introduced easily through the objective function, filters or the starting dataset.The mutation operator is composed of 7 general atom centred actions that define an interpretable neighbourhood on the molecular graph. As the exploration process only depends on this operator, it becomes thoroughly traceable and allows for chemically meaningful visualisations. This interpretability will be useful for further fine-tuning of the exploration process. The optimum found with EvoMol highlighted several limitations on the commonly used objective functions. For instance, we have found that using fingerprints can lead to counter-intuitive distances between molecules.EvoMol shows good performances in optimisation but for a practical application this is not satisfactory, since the quality of the compounds is an essential criterion. Evaluating the quality of a molecule is for the moment either very subjective or an imperfect measurement and it is an active research field. This is also the weakness of evolutionary methods in general . For druThanks to the tree visualisation, we could observe how EvoMol builds and improves upon the furane core like an experimental chemist playing very efficiently with substitutions and positions and then intensifying on promising candidates. Since the synthesizability prediction is still a complex issue, we believe that this related solution tree could be a useful tool to discuss chemistry. It brings a definite added value compared to a simple portfolio because it explains the trial-and-error of the exploration and the proximity of the proposed solutions.In the future, we believe our method would benefit from a diversity mechanism. It would help to provide high scoring individuals in various areas of the chemical space. It should be configurable in order to choose a compromise between exploration and intensification depending on the objective. We also consider that EvoMol could profit from reinforcement learning to select actions depending on the context. This should limit the number of calls to the evaluation functions, especially in the case of a costly objective function.Additional file 1. List of the 457,139 SMILES of the ChEMBL-like dataset with their corresponding CLscore.Additional file 2. Archive of the GuacaMol benchmarks experiments.Additional file 3. Proportion of generated solutions passing GuacaMol quality benchmark.Additional file 4. Representation of the best solutions found on GuacaMol MPO benchmarks.Additional file 5. Boxplot of all 20 goal-directed GuacaMol benckmarks scores obtained on 10 executions of each experiment with EvoMol. Experiments using all actions, using only primary actions and starting from methane are represented in blue, orange and green respectively.


Kaposi’s sarcoma (KS) is a cancer that often affects individuals with human immunodeficiency virus, acquired immunodeficiency syndrome (AIDS), those who have received an organ transplant, or others who are immunocompromised. KS is a vascular tumor that most often presents in cutaneous sites, including the lower extremities, oral mucosa, and genitalia. Literature regarding KS with ocular involvement is scarce. We present a rare case in which a patient diagnosed with AIDS-associated KS exhibited ocular and diffuse manifestations. The lesions of cutaneous KS are frequently mistaken for an alternative diagnoses; therefore, the clinician should have a high index of suspicion for this vascular tumor in AIDS patients.  Kaposi’s sarcoma (KS), a vascular tumor associated with human herpes virus 8 (HHV-8) infection, is the most commonly seen neoplasm in patients with acquired immunodeficiency syndrome (AIDS) . It typi3). Abdominal imaging on presentation revealed diffuse retroperitoneal, iliac, pelvic, and inguinal lymphadenopathy and findings suggestive of proctitis. He was treated with antibiotics for the presumed proctitis; he responded well. The infectious diseases service was consulted, and the patient agreed to follow-up as an outpatient. The colorectal surgery department was also consulted for further evaluation, monitoring, and treatment. One month later, the patient was started on antiretroviral therapy (ART). At the surgeon’s office, perianal lesions were noted, which were thought to be condyloma acuminata. The decision was made to allow time for the patient’s CD4 cell count to increase prior to excision and fulguration of the presumed condylomas. A 23-year-old, bisexual, cisgender male presented to the emergency department (ED) with left groin swelling and perirectal pain that had been ongoing for five days. He was predominantly involved with men, and last had anal-receptive intercourse three months prior. His last human immunodeficiency virus (HIV) screen had been negative five years prior. However, on this admission he was diagnosed HIV positive  and with AIDS . During this admission, multiple biopsies were obtained, including from the anterior maxillary gingiva, left axillary lymph node, and perianal lesions. Gingival biopsies showed mitotic activity with spindled cells forming slit-like spaces with numerous extravasated red blood cells Figure .Immunohistochemical stains were strongly and diffusely positive for HHV-8 Figure  and CD313 with an undetectable viral load. A hematology-oncology consultation was obtained, and the recommendation was made to start the patient on doxorubicin and continue ART. Close follow-up with infectious disease, hematology-oncology, ophthalmology, and colorectal surgery was also recommended. Because our patient did not present with upper respiratory signs, we did not pursue pulmonary node biopsies due to risk of hemorrhaging with these highly vascular tumors. Instead, we opted for surveillance with imaging and treatment.An ophthalmology consult was obtained for suspicion of ocular KS. Comprehensive examination showed no abnormalities of visual fields, acuity, or extraocular movements. Ocular biopsy was not obtained due to risk of bleeding. His CD4 cell count at that time was 40 cells/mmKS is the most common neoplasm in patients with HIV and AIDS . KS has We found few documented cases and studies of KS with ocular involvement. A study of HIV/AIDS patients reported ocular KS in 0.25% of patients with KS diagnosed at other sites . Local tOur patient presented with anal KS lesions initially thought to be condyloma acuminata, illustrating that KS is frequently mistaken for other dermatologic conditions . ThroughOur patient was started on ART, with a resulting increase in his CD4 cell count; however, he developed a rapid, aggressive, and diffuse form of KS associated with IRIS that included multiple systems throughout his body. In some patients, initial development of a tumor or tumor exacerbation occurs after the initiation of ART; this may be due to IRIS . GlucocoThe outcomes for patients with KS are difficult to describe and predict due to its highly variable course, and although no randomized control trials exist, observational studies suggest that earlier detection of KS may be more beneficial . We wereIn patients with HIV and/or AIDS, a high index of suspicion for KS should be maintained for masses, bleeding tissue, oral mucosa changes, and/or gingival enlargement. There can also be involvement in atypical sites, such as the conjunctiva, as in our patient. Although often misdiagnosed, KS can be confirmed through biopsy and molecular testing for HHV-8.


Phonons are the main source of relaxation in molecular nanomagnets, and different mechanisms have been proposed in order to explain the wealth of experimental findings. However, very limited experimental investigations on phonons in these systems have been performed so far, yielding no information about their dispersions. Here we exploit state-of-the-art single-crystal inelastic neutron scattering to directly measure for the first time phonon dispersions in a prototypical molecular qubit. Both acoustic and optical branches are detected in crystals of [VO(acac) Molecular nanomagnets have potential applications for storing both classical and quantum information, with benefit of the high scalability of chemical synthesis. Here the authors use state-of-the-art experimental and theoretical methods to investigate phonons in a molecular qubit candidate. The use of molecular nanomagnets (MNMs) as classical bits relies on their slow relaxation of the magnetisation, which is undermined by spin-phonon interactions13. Molecular vibrations may also play an important role in determining the magnitude and temperature dependence of coherence times in molecular qubits14, which need to be very long to implement quantum algorithms.The two main pillars of the current research in molecular magnetism are the possibilities of exploiting molecules as classical bits for high-density magnetic memories17. As also pointed out in a recent critical perspective on the topic18, the key to construct a reliable model of phonon-induced relaxation dynamics in MNMs is to have access to phonon dispersions. In fact, several mechanisms take part into relaxation dynamics of MNMs , and the interplay between them depends on the phonon spectrum. Since experimental results on phonon dispersions were not available so far, many relaxation theories on MNMs have relied on the simple Debye model26. Even if they have been successful in understanding nuclear magnetic resonance (NMR) or dynamical susceptibility signals in some systems29, the fundamental limitations of the Debye model prevent a quantitative description of relaxation dynamics in the new generations of MNMs30. Moreover, phonon eigenvectors are necessary for the evaluation of spin-phonon coupling coefficients, which requires a full description of molecular vibrations, including atomic displacements due to accessible phonon modes. In particular, the possible presence of low-lying optical phonons producing sizeable intra-molecular distortions can be crucial for magnetic relaxation31. Furthermore, anti-crossings (ACs) between these low-lying optical branches and acoustic phonons, which can be experimentally detected only by measuring phonon dispersions, are also important for magnetic relaxation. While single molecules could be the long-term goal for applications, the majority of experimental studies on the relaxation dynamics of MNMs are performed in crystals or polycrystalline samples. In addition, the use of magnetically diluted single crystals32 can bring advantages in quantum simulation protocols, where the ensemble measurements immediately yield expectation values of the observables. Hence, the combination of an experimental technique directly addressing phonon dispersions and eigenvectors of a MNM crystal with state-of-the-art ab initio calculations is the starting point to investigate the physics behind relaxation mechanisms and benchmark theoretical models.Despite their importance, very limited experimental investigations on phonons in MNMs have been performed so far. Indeed, only integrated information on their low-energy spectrum or 33 and the LET spectrometer34 to directly measure for the first time phonon dispersions in a molecular qubit prototype. Indeed, INS is a very powerful technique to study phonons, because it enables a direct access to phonon eigenvalues and eigenvectors. Moreover, the recent advent of spectrometers combining the time-of-flight technique with position-sensitive detectors makes measuring the four-dimensional scattering function 36. This experimental method is largely applied to study phonon dispersions in inorganic systems with extended structures41, but it has never been applied to complex molecular crystals. This work focuses on VO-acetylacetonate ( was obtained by reaction of a basified (NaOD 99d7)2] was filtered and recrystallised in inert atmosphere with deuterated acetone-d7)2] was estimated by electron spray ionisation mass spectrometry, and it was found to be 98[VO(acac-dmentclass2pt{minim34. LET is a direct geometry spectrometer with The 4D-INS experiments on [VO(acac)Z and Y directions and a smaller portion in the X one mentclass2pt{minimTwo incident neutron energies of 7.3 and 13 meV were selected in repetition rate multiplication mode, with an energy resolution  of 0.23 and 0.55 meV at the elastic line, respectively. All measurements were performed at 62 at the level of DFT with the Perdew–Burke–Ernzerhof functional63 including Grimme’s D3 vdW corrections65. Indeed, the requirement of vdW-corrected functionals for the modelling of molecular crystals is by now confirmed and settled by several results in literature55. A double-zeta polarised (DZVP) MOLOPT basis set and a 600 Ry of plane-wave cutoff were used for all the atomic species. All the translational symmetry independent force constants were computed by finite difference approach with a 0.01 Å atomic displacements.All the structural optimisation and Hessian calculations were performed with the CP2K softwareThe optimisation of the isolated molecule has been done with a plane-wave cutoff of 850 Ry and by turning off the periodic boundary conditions. An integration step of 0.01 Å was used for the calculation of the isolated molecules force constants.ith atom of jth eigenvalue and eigenvector of the Hessian matrix at the q point. The Cartesian derivatives 57.The coefficients 66The 4D-INS technique is named after the possibility to measure the four-dimensional scattering function The structure factor 67 and measurements for different rotation angles were combined using HORACE46, yielding four-dimensional Z and transverse X and Y modes with Time-of-flight data reduction were performed with Mantid analysis suiteData simulations were performed by calculating the scattering cross-section in Eq.  with DFTentclass1pt{minimaSupplementary InformationPeer Review File


Strong evidence also points to a role for SFA as treatment for various cancers. Paradoxically, then SFA has the ability to enhance cell survival, and with conditions of cancer, enhance cell death. Given our findings of the benefit of SFA/Broccoli Sprouts as a dietary supplement during pregnancy, with improvement to the fetus, it is important to determine the beneficial and toxic dosing range of SFA. We therefore explored, in vitro, the dosing range of SFA for neuronal and glial protection and toxicity in normal and oxygen/glucose deprived (OGD) cell cultures.Perinatal brain injury results in neurodevelopmental disabilities (neuroDDs) that include cerebral palsy, autism, attention deficit disorder, epilepsy, learning disabilities and others. Commonly, injury occurs when placental circulation, that is responsible for transporting nutrients and oxygen to the fetus, is compromised. Placental insufficiency (PI) is a reduced supply of blood and oxygen to the fetus and results in a hypoxic-ischemic (HI) environment. A significant HI state in-utero leads to perinatal compromise, characterized by fetal growth restriction and brain injury. Given that over 80% of perinatal brain injuries that result in neuroDDs occur during gestation, prior to birth, preventive approaches are needed to reduce or eliminate the potential for injury and subsequent neuroDDs. Sulforaphane (SFA) derived from cruciferous vegetables such as broccoli sprouts (BrSps) is a phase-II enzyme inducer that acts via cytoplasmic Nrf2 to enhance the production of anti-oxidants in the brain through the glutathione pathway. We have previously shown a profound in vitro, the condition experienced by the fetal brain due to PI. We developed a cell culture model of primary cortical neuronal, astrocyte and combined brain cell co-cultures from newborn rodent brains. The cultures were exposed to an OGD environment for various durations of time to determine the LD50 (duration of OGD required for 50% cell death). Using the LD50 as the time point, we evaluated the efficacy of varying doses of SFA for neuroprotective and neurotoxicity effects. Control cultures were exposed to normal media without OGD, and cytotoxicity of varying doses of SFA was also evaluated. Immunofluorescence (IF) and Western blot analysis of cell specific markers were used for culture characterization, and quantification of LD50. Efficacy and toxicity effect of SFA was assessed by IF/high content microscopy and by AlamarBlue viability assay, respectively.OGD simulates, p<0.05) for astrocytes and co-cultures. Significant toxicity ranges were also confirmed in OGD cultures as ≥ 100 μM (p<0.05) for astrocytes, ≥ 50 μM (p<0.01) for co-cultures, but not toxic in neurons; and toxic in control cultures as ≥ 100 μM (p<0.01) for neurons, and ≥ 50 μM (p<0.01) for astrocytes and co-cultures. One Way ANOVA and Dunnett’s Multiple Comparison Test were used for statistical analysis.We determined the LD50 to be 2 hours for neurons, 8 hours for astrocytes, and 10 hours for co-cultures. The protective effect of SFA was noticeable at 2.5 μM and 5 μM for neurons, although it was not significant. There was a significant protective effect of SFA at 2.5 μM (Our results indicate that cell death shows a trend to reduction in neuronal and astrocyte cultures, and is significantly reduced in co-cultures treated with low doses of SFA exposed to OGD. Doses of SFA that were 10 times higher were toxic, not only under conditions of OGD, but in normal control cultures as well. The findings suggest that: 1. SFA shows promise as a preventative agent for fetal ischemic brain injury, and 2. Because the fetus is a rapidly growing organism with profound cell multiplication, dosing parameters must be established to insure safety within efficacious ranges. This study will influence the development of innovative therapies for the prevention of childhood neuroDD. Perinatal brain damage refers to injury that occurs from approximately 24 weeks gestation to 1 month after birth. 80–90% of injuries that result in cerebral palsy and other developmental disabilities, occur in utero, before birth . There aPBI results in a spectrum of neurodevelopmental disabilities (neuroDDs) that have lasting effects on a child’s life . These dIsothiocyanate, 4-methylsulfinylbutyl, is commonly known as Sulforaphane (SFA), and is derived from cruciferous vegetables, most prominently, broccoli sprouts –16. It iSFA has also shown promise in protecting the developing fetal brain in rat models of acute brain injury . SFA is in vitro to mimic the effects of PI .The relative cytotoxicity of different concentrations of SFA was established using an AlamarBlue (AB) assay. Using the REDOX indicator resazurin (oxidized form), it is possible to spectrophotometrically measure the cellular proliferation. Resazurin is blue and non-fluorescent, whereas resorufin (reduced form) is red/pink and highly fluorescent. Thus, measuring the changes in the fluorescence of the dye in the intracellular environment, modifications in the number of metabolic active cells can be detected. The AB assay was carried out according to manufacturer’s instructions. Cells were incubated with different concentrations of SFA (0 μM– 200 μM) using untreated cells (0 μM SFA) as control cells, after 24 hr of incubation AB solution (10% [v/v] solution of AB dye) was added into 100μl of complete media to each well. Wells containing only the AB solution/media without cells was used as the blank. Following 2 h incubation, AB fluorescence was quantified at the respective excitation and emission wavelength of 540 and 595 nm respectively, using a LumIstar Omega reader. Viability % was normalized: (sample relative fluorescent unit (RFU)–Blank) X 100/(Untreated cells RFU- Blank), using the untreated cells.Cells were washed with 1X PBS and treated with 4% paraformaldehyde (PFA)  for 15 mins to fix cells. Cells were washed again with 1X PBS, followed by treatment with 0.2% 100X Triton  in 1X PBS for 10 minutes to permeabilize cells. After washing with 1X PBS again, wells were blocked with 2% bovine serum albumin (BSA)  in 1X PBS at room temperature for 1 hour or overnight at 4°C, and then incubated with various primary antibodies at 4°C overnight. Wells were washed with 1X PBS, and then incubated with secondary immunofluorescent (IF) antibodies at room temperature for 1 hour. Cell characterization of co-cultures was established via IF cell images visualized using a laser scanning confocal microscope (Zeiss LSM710) and quantified using a high content analysis system, MetaXpress XLS. DAPI was used as a cell staining control and total cell count. Antibodies to the following proteins were used for this study: Anti-NSE, Anti-GFAP, Anti-CD68.p<0.05), **(p<0.01), ***(p<0.001), or ****(p<0.0001).GraphPad Prism 5 computer software was used. Data were from at least 3 experiments with a minimum of triplicates per experiment. Values were expressed as means ± SE. Statistical significance was analyzed using one-way ANOVA with Dunnett’s Multiple Comparisons Test. Significance is indicated by *(Immunofluorescence (IF) images show the characterization of neuronal cultures, astrocyte cultures, and co-cultures. Neuronal cultures show enhanced staining for NSE protein  comparedLD50 was defined as the duration of OGD that achieved equal to or above 50% cell death. The LD50 for each cell culture was determined by a Live/Dead assay, and cell death for each OGD duration was normalized to control (0h OGD). Increase in OGD duration showed significant cell death in neurons at 1, 2, 4, and 8 hours, compared to 0 hour OGD control . LD50 waOGD cultures at the previously determined time of LD50 were treated with SFA. The protective dose of SFA was determined as that which resulted in a significantly lower cell death due to OGD compared to control cell death (0 μM SFA). Cytotoxic doses of SFA was determined as the dose of SFA that resulted in a significantly higher cell death due to OGD compared to control cell death. In order to determine potential cytotoxic effects of SFA on brain cells in a normoxic/normal glucose environment, control cultures (no OGD) were treated with SFA, again at varying doses. Cytotoxic doses of SFA were determined as the dose of SFA that resulted in a significantly lower cell viability compared to 0 μM SFA. Cell viability, determined using AlamarBlue assay, shows that SFA had no effect on the viability of neurons, astrocytes or co-cultures at low concentrations . SFA at Live/Dead assay was also used to show cytotoxicity of SFA in control cultures. Cytotoxic doses of SFA were determined to be the dose of SFA that resulted in a significantly higher cell death compared to 0 μM SFA. SFA had no effect on the viability of neurons, astrocytes or co-cultures at lower concentrations . SFA wasThis study demonstrates the importance of dose dependent effects of SFA in different cortical brain cells. We show that low doses of SFA are protective in an OGD environment to PD2 cortical brain cell cultures and are safe in control cultures. On the other hand, high doses of SFA are cytotoxic under OGD and control normal oxygen and glucose conditions. Preventing cell death is key to the prevention of neurodevelopmental disabilities during pregnancy, as brain cell injury can lead to impaired cell survival, migration and connectivity that result in impaired motor, sensory, cognitive and behavioral functions. Conventional therapies, used at time of birth, have not been shown to be effective in reversing or repairing the brain damage that has already occurred. Hypothermia administered within a few hours after birth is only effective for injuries that occur during delivery, successfully slows down brain metabolism and reduces mortality, but has not been definitively shown to reduce CP incidence or severity . HypotheAlthough this study focuses primarily on the effect of SFA on cortical brain cells, perinatal brain injury can take place, often simultaneously, in both gray and white matter –9. A comGray matter injury is mainly due to cell death or functional compromise of neurons of the cortex, thalamus, and hippocampus; this is often also accompanied by damage to astrocytes ,9. Astroin vivo response may look like.The co-culture is most representative of the brain as it consists of all brain cell types extracted from the PD2 brain tissue. This would also explain why the LD50 time for co-cultures  was highThe Nrf2/ARE mechanism and its activation by SFA have been well established ,16,18–202O2 induced oxidative stress [Our study shows that SFA is safe and protective of brain cells in cultures at low doses (≤ 2.5 μM) while it is toxic at high doses. SFA has previously been shown to be a hormetic compound which exhibits a biphasic dose response. While the protective effect of SFA has been shown to work prominently through the Nrf2/ARE pathway, the toxic effect of SFA is impacted by various other mechanisms that result in cell death –35. We he stress . In addie stress –38.From the literature it is evident that there may be a shift in SFA mechanism from protective to toxic in a dose dependant manner. At very low doses near 2.5 μM, SFA is cytoprotective as shown in this study and previously reported in the literature ,36–38. AThe in vitro cell culture model used in this study has limitations. All cell cultures were prepared at P2. Clearly, in-vitro cell culture studies do not exactly reflect an in-vivo full tissue environment. However, it is important to reflect on the goals of our study, which were to: 1. Determine if there is a differential cellular effect of SFA on individual brain cells, and 2. Determine the range of safety vs toxicity of SFA, given the paradoxical benefits of SFA in neuroprotection and cancer therapy. This latter goal is especially important given our laboratory findings of the benefit of SFA as a dietary supplement during pregnancy for the prevention of perinatal brain injury and childhood disability. In this regard, the fetus is a rapidly developing organism which has characteristics of both cell injury (PI) and cell division . Hence, understanding the boundaries of dosing is extremely important. Finally, our co-cultures were done in order to best assimilate the combination of cells found in the brain, as well as the extracellular environment of the cells.in vitro using mammalian cultures from this study; and mechanistic effects in each cell type along with co-cultures from this project will be investigated. Next steps will involve investigating effects of SFA during pregnancy on the potential for teratogenicity or organ damage in preclinical animal models; a step required to determine a safe and effective dose that can be translated to human pregnancy clinical trials.In conclusion, we have determined that low doses of SFA in neuronal, astrocyte, and co-cultures is neuroprotective in an OGD environment, and safe in control cultures. High doses of SFA are toxic in all cultures in both OGD and control environments. It is important to note the difference between effective low protective dosing and high toxic dosing of SFA are at least a 10-fold difference which alludes to the safety in using SFA as a preventative approach in a perinatal setting. The Nrf2/SFA mechanism has been extensively research and is available in literature; in this study we extrapolated knowledge from the literature to explain effects of SFA in our neuron, astrocyte, and co-cultures ,16,18–20S1 FigA) Neuronal cultures did not show significant toxicity, B) Astrocyte cultures showed toxicity of SFA ≥ 50 μM, C) Co-cultures showed toxicity of SFA ≥ 200 μM. Data represented as Mean±SEM, n≥3, One way ANOVA, and Dunnett’s Multiple Comparison Test was completed for all cultures; *p<0.05, **p<0.01, ***p<0.001, ****p<0.001, compared to respective controls (0 μM SFA).(TIF)Click here for additional data file.S1 Raw images(PDF)Click here for additional data file.


Antimicrobial properties of the functional nanofibers were estimated by using Gram-negative/positive bacteria. The cytotoxicity of the functional nanofibers was studied using fibroblast cells. Furthermore, this study investigated how long the shelf-life of tomatoes was extended. The nanofibers could serve as a multifunctional packaging, as an emerging technology in agricultural products, and even contribute to a better quality of various distributed agricultural products.Nanofibers made by electrospinning are being applied to an unlimited number of applications. In this paper, we propose the fabrication of antimicrobial functional nanofibers infused with essential oil for packaging applications that can extend the shelf-life of fruits. The morphology of nanofibers with different concentrations of essential oil was characterized by SEM and mechanical enhancement was confirmed via universal testing machine (UTM). The surface chemistry and crystalline of the nanofibers were investigated by FTIR and XRD, respectively. The CO Electrospinning, which was first used in 1934 and has been actively studied for over 80 years, is a facile method used to produce nano-sized structures in which a high voltage is applied to an electrically charged polymer solution to form a Taylor cone by mutual electrostatic repulsion between surface charges and Coulombic force ,3,4. NanMelaleuca alternifolia [Use of tea tree oil (TT oil) extracted from rnifolia  began inrnifolia ,12. It hrnifolia ,14,15,16rnifolia ,18. Ther2), the prevention of external moisture infiltration, as well as the prevention of decay by bacteria of the fruit through proper surrounding environment [2 reduction effect and moisture prevention effect, to be applied in a variety of other fields, such as packaging, filters and biomedical application.In this study, we applied functional nanofibers to packaging to study the reduction of discharged carbon dioxide  solutions dissolved by dimethylformamide  and tetrahydrofuran  in 1:1 volume ratio which containing 0, 1%, 3% and 5% of TT oil were prepared, to which a voltage of 15 kV was applied to produce nanofibers by electrospinning. To prepare the packaging container for study, after punching a circular hole of 5 cm in diameter in the packaging container, we attached the nanofibers to complete the sample of the packaging container.Before proceeding with the experiment, the sample was prepared as shown in 2) reduction test was carried out through a hand-made experimental apparatus. This hardware of hand-made apparatus consists of a sensor part, chamber and CO2 circulator part. The software was based on the LabVIEW program.The morphology of the nanofibers according to the oil content was observed by scanning electron microscope . The histogram of fiber diameter was drawn by measuring more than 50 nanofibers randomly from the SEM images using Image J program. The mechanical properties of the nanofiber were obtained using a universal test machine  using a dog bone specimen according to the ASTM D638 protocol ,22,23,24Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) [5 colony forming units for each bacteria with 9 mL of LB solution. The bacterial solution was suspended on the nutritive agar plate, and the samples were carefully placed on the inoculated plates. The agar plates with samples were incubated at 37 °C for 24 h and all antibacterial tests were performed in triplicate. The inhibition area measurement was executed by using ImageJ software. The zone of inhibition follows a standard.In vitro antibacterial activity of the samples was determined by growth inhibition study method using  aureus) . Three t2 and 95% humidity. Prepared specimens were fixed in the wells of a 48-well cell culture plate  and sterilization under UV radiation for overnight. The cells with a density of 20,000 cells/well were seeded on the samples by pipetting onto the center. Each sample was cultured with cells for 1, 3 and 5 days and evaluated using cell counting kit-8 (CCK-8) in a 48-well plate.The cytotoxicity of the samples was estimated using fibroblast cells (NIH-3T3). The cells were cultivated in the cell culture plate with Dulbecco’s modified Eagles medium  including 10% fetal bovine serum  and 1% penicillin/streptomycin in the incubator at 37 °C with 5% COTo observe the degree of spoilage between the three different types of packaging, six tomatoes were prepared. The samples were randomly assigned and stored in each type of packages. The samples were stored for 14 days at around 30 °C.n = 3. Statistical significance has assessed the level of significance with a one-way ANOVA followed by a Tukey test for means comparison by employing the OriginPro 8.5 software (p < 0.05).All images were analyzed with ImageJ software. Results are presented as the mean ± standard deviation (SD) for −1 [Nanofibers can be applied to a variety of applications due to their many small pores and large surface area. In this study, we fabricated functional nanofibers and used it in packaging applications. In order to find an appropriate concentration of TT oil, we compared the morphology and mechanical strength of the nanofibers with different concentrations of TT oil. As can be seen from −1 . CompariEscherichia coli  and Staphylococcus aureus  to determine the antimicrobial properties of nanofibers containing 5% of TT oil [The bacterial experiment was carried out using f TT oil ,28. In F2 in packaging, one of the major factors of the proper internal air to extend the shelf-life of the fruit, we made the device depicted in 2 reduction of the control (no nanofibers) with our prepared nanofibers (PU-5% TT oil). 2 was introduced CO2 increased immediately, whereas when nanofibers were installed, the inflow of CO2 started with a smaller amount after a few seconds delay. Second, comparing the tilt graph of carbon dioxide inflow over time, it could be seen that the slope of the increase of CO2 when the nanofiber was installed was low. Finally, when the nanofibers were used, the increase of CO2 was stopped before the completion of the CO2 inflow. All of these facts mean PU-5% TT oil sample could be reduced the entrance of carbon dioxide into the package and it could maintain a proper environment for fruits. Therefore, the use of PU-5% TT oil was expected to reduce the amount of CO2 in the fruit packaging, and thus help the fruit maintain its initial state.To maintain the fruit in good condition, the air composition inside the packaging is also important. To measure the concentration of COThe contact angle results of the nanofibers are shown in 2 reduction test and antibacterial test. Especially, antibacterial tests proved that tea tree oil could still have antimicrobial properties even if it was fabricated into a nanofiber. In addition, the biocompatibility, one of the most important factors in packaging application, was tested by CCK-8 assay using fibroblast cells. In order to test whether the functional nanofiber was actually effective, an observational examination was carried out by storing them at room temperature for 14 days using tomatoes. Furthermore, nanofibers infused with TT oil were expected to be applied not only to fruit packaging, but also to other applications requiring antimicrobial activity such as filter and medical applications.In summary, we prepared nanofibers based on tea tree essential oil by the electrospinning technique with antimicrobial, enhanced mechanical and moisture protection properties that could prolong fruit shelf-life. The characterizations and evaluations of all functional nanofibers were verified by experiments such as mechanical test, CO


C. elegans vulva is formed from divisions of three vulval precursor cells (VPCs) – P5.p, P6.p, and P7.p – arranged along the anteroposterior axis in the ventral epithelium . Previous analyses show the orientation of P5.p and P7.p descendants is determined by the interaction of multiple Wnt signals. Specifically, in the absence of all Wnts, the VPCs display a randomized orientation, which is likely the default . Two separate Wnts from the anchor cell, LIN-44 and MOM-2 acting through receptors LIN-17/Frizzled and LIN-18/Ryk, respectively, regulate P7.p orientation . In the absence of these signals the orientation of the progeny of P7.p mimic those of P5.p and face toward the posterior of the worm, a phenotype referred to as posterior-reversed vulval lineage (P-Rvl). This posterior orientation is dependent on the instructive signal EGL-20, a Wnt expressed in the tail acting through CAM-1/ROR and VANG-1/Van Gogh, and is referred to as “ground polarity” .The lrp-2, and its role in controlling the orientation of P7.p daughter cells. To investigate this interaction double mutants were constructed with both alleles of lrp-2 and lin-17(n671) (Table 1). Much like cam-1(gm122) and vang-1(ok1142), both alleles of lrp-2 suppress the lin-17(n671) phenotype from 74 to approximately 50% P-Rvl leading us to hypothesize that lrp-2 functions in the same pathway as cam-1 and vang-1. Furthering this hypothesis we have shown that, like cam-1 and vang-1, lrp-2 controls the localization of SYS-1/b-catenin . To ensure that this phenotype was a result of loss of lrp-2 function as opposed to background effects we injected a fosmid (WRM0617cA02) containing the full-length sequence of lrp-2 and found that it does rescue the double mutant phenotype of lin-17(n671); lrp-2(gk272) from 55 to 73%. In order to better test this hypothesis a triple mutant was constructed between lin-17(n671), lrp-2(gk272), and cam-1(gm122) (Table 1). This triple mutant displays the same P-Rvl penetrance as both the lin-17(n671); lrp-2(gk272) and lin-17(n671); cam-1(gm122) double mutants confirming that lrp-2 functions in the same pathway as cam-1.Here we examine the role of a low-density lipoprotein receptor, Strains were constructed by standard procedures .Strains:N2MT1306: lin-17(n671) PS4818: lin-18(e620)PS3976:lin-17(n671)/ hT2 [qIs48 (myo-2::gfp etc.)]; +/ hT2 [qIs48]; lin-18(e620)PS5401: egl-20(hu120)PS5530: lin-17(n671); egl-20(hu120)NG2615: cam-1(gm122)RB1125: vang-1(ok1142)VC543: lrp-2(gk272)VC621: lrp-2(gk292)PS4809: lin-17(n671); cam-1(gm122)PS5651: lin-17(n671); vang-1(ok1142)lin-17(n671); lin-18(e620) animal awere segregated from PS3976.lin-17(n671); lrp-2(gk292) double mutant was constructed by crossing lrp-2(gk292) males with strain MT1488: lin-17(n671); unc-13(e1091) hermaphrodites.The lin-17(n671); lrp-2(gk272) double mutant constructed by crossing lrp-2(gk272) males with strain MT1488: lin-17(n671); unc-13(e1091) hermaphrodites.The lin-17(n671); lrp-2(gk272); cam-1(gm122) Triple mutant constructed by crossing lin-17(n671); lrp-2(gk272) hermaphrodites with cam-1(gm122) and sequencing for homozygous triples.PS6581: qIs95[pSYS-1::VENUS::SYS-1 with pttx-3::dsRed as coninjection marker];PS6576:lin-18(e620) sem-5(n1779)PS6580: qIs95; sem-5(n1779)PS6579: Pegl-17::CWN-1::GFP (unnamed construct) in cwn-1(ok546); lin-18(e620)


The rapid evolution of the COVID-19 pandemic has underscored the need to quickly disseminate the latest clinical knowledge during a public-health emergency. One surprisingly effective platform for healthcare professionals (HCPs) to share knowledge and experiences from the front lines has been social media . However, identifying clinically-relevant content in social media without manual labeling is a challenge because of the sheer volume of irrelevant data. We present an unsupervised, iterative approach to mine clinically relevant information from social media data, which begins by heuristically filtering for HCP-authored texts and incorporates topic modeling and concept extraction with MetaMap. This approach identifies granular topics and tweets with high clinical relevance from a set of about 52 million COVID-19-related tweets from January to mid-June 2020. We also show that because the technique does not require manual labeling, it can be used to identify emerging topics on a week-to-week basis. Our method can aid in future public-health emergencies by facilitating knowledge transfer among healthcare workers in a rapidly-changing information environment, and by providing an efficient and unsupervised way of highlighting potential areas for clinical research. The resIn the face of a developing medical situation such as COVID-19, health-care professionals (HCPs) interact with a range of knowledge sources to provide and share up-to-date, accurate clinical information. Guidance released by public health organizations such as the World Health Organization (WHO) and the US Centers for Disease Control and Prevention (CDC) is considered the most reliable, but is relatively slow to change due to its wide impact. These guidelines are backed by published research and case reports, which also take time to be disseminated due to the need for formalization and peer review. To obtain more up-to-the-minute information, HCPs share insights amongst each other through webinars, hospital-specific channels, and chat groups. For example, many initial accounts of Chilblain-like skin lesions on the toes, a now-famous symptom of COVID-19, were circulated on a WhatsApp group from France .Social media platforms have emerged as important areas for sharing clinical information publicly. In particular, Twitter is a popular option because it is already home to a sizeable physician community , 25. HCPFor HCPs looking for clinically-relevant advice or anecdotes, it can be difficult to find the most relevant authors unless they are already in the right social circles. Furthermore, because of the high volume of non-expert conversation, the terms that one would expect to find in clinically-meaningful information can also be found in mundane and non-expert posts as well as in myths and misinformation . In the 1.1clinically relevant if it is technical in nature and intended to help characterize, prevent, diagnose, or treat the disease under consideration. This definition helps to characterize and remove irrelevant information, especially given the low proportion of clinical tweets compared to noise. While we exclusively consider COVID-19 and HCP-authored Twitter data in this study, the problem formulation and approach can be applied to other healthcare topics or social media platforms.Framed as an information retrieval problem, our task is to extract and cluster clinically relevant social media posts by reputable authors, who form a tiny minority of the general population. For the purposes of this study, we define information as all posts, including irrelevant ones, some upfront labeling and filtering is still typically required  and retaining topics that satisfyRi). We decided to expand the dataset in D(1) by including the complete threads, because the missing tweets often appeared to contain useful clinical information despite not explicitly mentioning COVID keywords. The final HCP-authored tweet set contained 990,756 threads, with 1,078,830 total tweets.We illustrate the use of our method on a publicly-available COVID-19 Twitter dataset , comprisWe validated the initial HCP filtering step  by samplk = 1000) without relevance filtering, the clinically-relevant topics were vastly outnumbered by irrelevant ones. This validated the need for filtering out tweets with spurious relevance and preferentially surfacing tweets like (a).As expected from the above analysis, the combined presence of non-HCP content and irrelevant content by HCPs resulted in tweets that vary dramatically in relevance, as illustrated in 3.2We performed three rounds of filtering on the HCP-authored dataset, resulting in a dataset of 107,794 tweets. Roughly 38–40 topics were selected as relevant in each iteration, but 85 topics would have been selected to proceed to the fourth iteration, indicating that most of the irrelevant data had been filtered out by this point.D(4)), shown in The topics extracted from the third level of filtering  and #29 (supporting evidence); these topics likely co-occur frequently with clinical terms. Topics that are correctly scored as irrelevant often tend to deal with the boilerplate aspects of clinical tweets, such as #91 (announcing study pre-prints), as well as topics adjacent to COVID-19 but not directly applicable . Interestingly, the topics considered least relevant (#99 and #100) are the ones that deal with surgical and everyday masks, respectively. These tweets are likely considered irrelevant because they often touch on the U.S. politicization of mask wearing, or address the topic in a public-safety announcement format, such as “COVID is still spreading out there. Wear your mask. Practice social distancing.” Irrelevant topics will always be present in some frequency because they co-occur in the same documents as relevant topics, but by presenting the topics in ranked order, the model still facilitates interpretation over an unsorted topic list.3.3We validated the performance of our iterative filtering technique by conducting a quantitative and qualitative comparison of topics generated from the final filtered set with those generated using traditional and seeded LDA approaches. These methods were tested on the HCP-authored tweet set, so the prevalence of clinical content was considerably higher than it would be in a random sample of the larger COVID-19 dataset.Concepts. Each topic was seeded with one of the most common single-word UMLS concepts in the filtered tweet set. The top 5 concepts were “lung,” “plasma,” “pneumonia,” “hydroxychloroquine,” and “ards.”Topics. Each topic was seeded with the top three words from one of the highest-scoring topics in the relevance-filtered 100-topic model. For example, the top three topics were “fever, symptom, cough,” “hydroxychloroquine, hcq, chloroquine,” and “sars, human, coronaviruses.”For traditional LDA, we used MALLET , the samk = 10, 20, and 50 topics to compute the two metrics2. The results, shown in k. Note that relevance filtering should necessarily produce more clinically relevant results than traditional LDA, since our method specifically filters for topics containing clinical concept mentions. However, it also performs better than SeededLDA, even when highly clinically-relevant words are provided to that method as seeds. Similarly, we find that relevance-filtered topics are the most coherent out of the four methods, while SeededLDA’s performance is somewhere between traditional LDA and relevance filtering.We quantitatively compared each of these four methods according to two metrics that roughly measure topic quality. The first was the fraction of the top 10 words for each topic that were annotated by MetaMap as a UMLS concept, which approximates the amount of clinical interest in the topic model as a whole. The second was UMass coherence, a well-established metric that aims to correlate with human judgments of topic interpretability . Each oflung, patient, risk, disease, high” and “symptom, illness, mild, home, stay” ; however, most of the SeededLDA topics have little to do with their seed words. Several topics share common words in the corpus, such as “pandemic” and “health.” Notably, the SeededLDA model initialized with top topics from the filtered topic model still failed to associate other clinical terms with the seeds . This suggests a lingering susceptibility to irrelevant content that would need to be mitigated in other ways if SeededLDA were used on this task.The observation of higher topic coherence for relevance filtering was confirmed in a qualitative comparison of the topic words generated by each method. Interestingly, traditional LDA produces several interpretable topics, such as “case, death, report, number, day” and “disease, infection, risk, flu, sars.” However, these topics are overall less clinically relevant than the model trained on the filtered set, which includes topics like “patient, pt, icu, ventilator, require” and “transmission, asymptomatic, spread, infection, contact.” Taken together, the quantitative and visual assessments of the four methods indicate that relevance filtering produces the most coherent topics overall, while traditional LDA and SeededLDA are roughly comparable . Relevance filtering likely eliminated numerous political and economic tweets, leading to the observed improvement in topic quality over traditional LDA.3.4concepts, but instead over all words in each tweet (excluding stopwords and words explicitly mentioning the coronavirus). This comparison therefore reflects the marginal benefit of directing the relevance filtering toward words already known to be clinically relevant (subject to MetaMap error).To validate our use of MetaMap concept annotations when calculating relevance, we ran a version of our iterative filtering routine that entirely omitted clinical concepts. In other words, the relevance of a topic  was compD(1) relative to D(0), suggests that heuristic author filtering alone establishes a fairly strong baseline, independent of the use of clinical concepts. Still, after three rounds of relevance filtering, the top phrases in D(4) show a marked improvement over D(1). Using concepts in the filtering process led to an emphasis on clinical content , while using all words resulted in a greater proportion of epidemiological content . This could be because of a natural bias in UMLS toward concepts used in a hospital setting, or because epidemiological topics received the most sustained attention while areas of medical interest shifted. Therefore, while using concepts better suited our objective of extracting clinically-relevant information in this case, omitting the MetaMap step in our pipeline could still result in useful filtering for a different application.First, we compared the words that were predicted to be most and least relevant by each method, shown in any two of the keywords were present in a tweet, its relevance could be gauged with relative certainty. For example, any tweet containing both “anosmia” and “dysgeusia” should most likely never be eliminated. Similarly, any tweet containing the names of political leaders is most likely irrelevant. A total of 26,851 tweets were used for this analysis.Next, to ensure our method was accurately discriminating relevant and irrelevant tweets, we examined the effect of filtering on several topics known to be either relevant or irrelevant to the pandemic. With the guidance of a clinician, 12 categories and associated keywords were chosen such that if 3.5before they appeared in academic articles.While the topic models analyzed above were built retrospectively on a dataset containing nearly six months worth of tweets, applying our method during the early stages of a pandemic would require a more real-time approach. We therefore investigated whether applying automatic relevance filtering to time-windowed subsets of the data could recover topics of clinical interest, or micro-trends, during those periods. This experiment also provided a natural opportunity to probe the time-scale differences between Twitter and academic articles, two information sources that evolved at different rates throughout the pandemic. We hypothesized that clinical keywords would be surfaced in topic models soon after their first mention on Twitter, and that they would appear in HCP-authored tweets and clinically-relevant topics k = 100 topics were generated after two rounds of relevance filtering on each subset. The resulting topics were highly granular and highlighted new clinical concepts from week to week, similar to the topics shown in To generate time-windowed topic models, we first split the dataset into twenty 2-week subsets, where the subsets overlapped each other by 1 week. Topic models with 3.5.1thrombosis, generally have even smaller tweet counts; however, as shown below, these tweets could still be found within other clinically-relevant topics. These results support the notion that relevance-filtered topic models can be a fairly sensitive indicator of clinical interest.Many of the keywords appear in the time-windowed topic models in the same week as or shortly after the first tweet that contains them (indicated by the upper black caret). This is a remarkable finding, given that several of these keywords are mentioned in fewer than 20 tweets per week . The cases in which topic model appearance is delayed from the first tweet mention, such as 3.5.2remdesivir appeared in almost all time-windowed topic models from Jan. 26 onward, while the first mention of the drug in CORD-19 was only in mid-February. Another example is the micro-trend discussing the use of ibuprofen to treat COVID-19 symptoms, which became popular and controversial in mid-March and was briefly addressed in a March 25 article. These cases support the usefulness of Twitter topics in surfacing clinical research with long lead times before publication, as well as potentially controversial and rapidly developing micro-trends.Next, we consider the question of whether the time-windowed topic models surface topics of interest in advance of academic publications. Note that this is only possible when the first tweets about a topic appear before the first publication, which occurred for six out of the twelve example topics. Even so, cytokine and ventilators predate their first appearance in the time-windowed topic models. This seems to be because the bulk of discussion of these topics in our English-language dataset does not begin until March, when COVID-19 first started to hit English-speaking countries. While early tweets mentioning these topics were present in the dataset, they were typically isolated and served to highlight publications describing the disease in early epicenters like China (e.g. [ARDS). This reflects a fundamental drawback to Twitter trend analysis: in order to appear in a topic model, the topic must be actively discussed by HCPs on Twitter, who are in some ways systematically non-representative of the global medical community. Another complication of this analysis is that some concepts  appear in both time-windowed topic models and publications at the very start of January, implying that our dataset only starts amid existing discussion of these topics.In contrast, we found that publications for the concepts related to na . On the other hand, MetaMap concept extraction can identify relevant phrases regardless of their frequency, a useful complement to statistical NLP methods. Using these annotations to rank the topic models allows one to quickly discard irrelevant categories, improving interpretability considerably for larger models. Concept extraction therefore approximates a physician’s prior belief of which topics should be considered An iterative approach is key to enabling topic modeling and concept extraction to refine and validate each other’s results. For example, in early iterations, we observed many tweets that were associated with relevant topics because they contained clinical terminology, but that were not themselves written in a medical “frame.” As these tweets were carried forward into subsequent levels, however, topics became more relevant overall, and tweets that used clinical terminology in a non-medical context became sequestered into their own topics. We note that the filtered topic sets do contain false positives, but their prevalence dramatically decreases over the course of filtering.AuntMinnie.com . This was especially the case for early clinical topics, perhaps because they originated in non-English language countries, as well as topics stemming from biological research (e.g. the role of the ACE2 receptor). In later months, the dataset includes more anecdotal discussions that document the English-speaking medical community’s evolving understanding of COVID-19. By surfacing both timely references to published findings and records of real-time clinical developments, topic models of HCP-authored tweets could greatly accelerate awareness of new developments outside of the circles in which they are shared.The volume and diversity of clinically-relevant content found in this study is a testament to the opportunity for medical professionals to learn from each other and initiate new lines of research based on topics extracted from Twitter. Our filtered dataset seems to capture micro-trends of special interest to physicians such as emerging symptoms and clinical anecdotes, which augment and enrich an understanding gained from academic articles. In fact, the first tweets in these topics of interest often themselves contained links to publications, including on domain-specific platforms such as The relevance filtering strategy presented here suggests future research questions that can take advantage of the scale and high signal-to-noise ratio of data it generates. In particular, many downstream linguistic analyses, such as clinical concept co-occurrence or sentiment analysis, would benefit from a dataset that is highly focused on medical content. Time-limited topic models such as the ones described in As with any study involving Twitter data, our analysis is subject to the biases and caveats inherent in social media. The dataset collected here only consisted of English tweets, but it could be more helpful to apply the technique across languages and capture a truly global conversation, perhaps by integrating a multilingual topic model . Even am5We present a method that combines topic modeling and clinical concept extraction to surface clinically relevant information from a noisy text dataset. Both topic modeling and concept annotation have their limitations on this type of data; nevertheless, we have shown that iterating between the two techniques can overcome these weaknesses. This is especially important in emergent situations such as COVID-19, where unconventional data sources and unsupervised information extraction are often the only option for rapid analysis. Our pipeline can be applied without modification to social media data on other medical topics, and the iterative filtering technique could be a helpful augmentation to topic models used for preliminary explorations of text data.In seeking to extract clinical information from social media data, this study addresses a problem space that has not yet been addressed to our knowledge. Indeed, in normal circumstances the rapid fluctuations of social media trends are antithetical to robust, reliable official guidance. As demonstrated by our analysis, however, HCP-authored tweets about COVID-19 can present a surprisingly bountiful window into the epicenters of a pandemic, and we hope that our method enables future research to gain deeper insights from the physician population on social media. By automatically bringing clinical tweets out of the limited audiences among whom they are shared, newly-emerging clinical observations can be disseminated quickly and clinicians everywhere can contribute to shared knowledge. Just as Twitter data reflects the rapidly-changing world, this method could enable the flexible, real-time analysis that a pandemic demands.


Kounis syndrome (KS) is an acute coronary event secondary to an allergic reaction. It is provoked by environmental agents, food, and medications. KS is caused by the release of allergic mediators. We are reporting a case of a 39-year-old man who had a syncopal episode after he took cephalexin and ibuprofen for toothache. He developed chest pain and erythematous rash later. His electrocardiography did not show any ST-segment elevation changes and cardiac troponins were elevated. He was started on the acute coronary syndrome treatment protocol. Coronary angiography revealed no significant obstructive or culprit lesions. The patient was discharged home in stable condition. He is advised to adhere to lifestyle modification and outpatient follow-up with cardiology and allergy/immunology. KS is infrequently reported in the medical literature. Physicians should pay attention to any allergic reaction preceding the acute cardiac event and consider KS in the differential diagnosis. Kounis syndrome (KS) is an acute myocardial infarction (MI) triggered by allergic reaction or anaphylaxis provoked by medications, food, or environmental triggers. The most common causes are antibiotics and insect's bites . KS is aA 39-year-old Caucasian male presented with a known medical history of type 2 diabetes mellitus, hypothyroidism, obesity, dyslipidemia, and tobacco smoking. He recently had a toothache and dental infection. The patient was evaluated in the ED with syncope, chest pain, and symptoms suggestive of a possible allergic reaction after taking the first doses of cephalexin and ibuprofen. The patient was brought to the ED by his family after a witnessed syncopal episode at home. According to his family, three minutes after taking the medications, the patient vomited, and started having numbness in his lips and arms along with blurry vision and lightheadedness. The patient then fainted for seconds and regained consciousness in less than a minute.2) of 80%, and hypotension with a blood pressure of 90/60 mmHg. He became lethargic and confused and developed a generalized itchy skin rash. He received intramuscular injection of epinephrine with the concern of allergic reactions.En route to the hospital, he reported a chest pain that was associated with profuse sweating. He was given sublingual nitroglycerin, aspirin, and morphine. The chest pain resolved shortly. Upon initial assessment in the emergency room (ER), the patient had an episode of hypoxia with oxygen saturation  showed normal sinus rhythm, without significant ST elevation Figure . Labs shThe patient was started on an acute coronary syndrome protocol for non-ST elevation myocardial infarction (NSTEMI). He underwent cardiac catheterization, and his coronary angiography did not show any evidence of coronary artery disease or obstructive lesions Figure .No intervention was performed. His echocardiogram revealed normal left ventricular function without evidence of structural heart disease. The patient's clinical presentation was believed to be due to coronary vasospasm in a setting of allergic reaction consistent with KS type 1. The patient was treated medically with aspirin, and high-intensity statin for primary prevention of coronary artery disease. He was also advised and counseled about lifestyle modification in addition to avoidance of cephalosporins. KS is an underrecognized cause of allergic vasospastic acute coronary events. According to a recent review article  publisheThe pathophysiology of KS entails allergic reactions causing the release of inflammatory mediators, including histamine, neutral proteases, arachidonic acid products, platelet-activating factor, cytokines, and chemokines . The conAs we mentioned earlier, it has three subclasses and type 1 was the most common 72.6%) followed by type 2 (22.3%) and type 3 (5.1%) [.6% folloOur patient's clinical presentation is likely due to the KS type 1 variant as he has no evidence of obstructive lesions on cardiac catheterization. Key factors that led to identifying this patient to have KS included exposure to potential allergen followed by acute anginal episode and erythematous skin rash. Previously, case reports have found an association with cephalosporins, including cefazolin , as wellThe acute management of KS relies on subtype. The most used medications in type 1 are steroids and antihistamines for mast cell stabilization to control the allergic reaction and end the response cascade . Fluid rIn the other subgroups 2 and 3), treatment of the coronary event should be similar to other causes, including both medical and interventional management according to the most recent acute coronary syndrome (ACS) guidelines  and 3, t. Among aKS has a good outcome, and it is associated with rapid recovery and fewer complications. Serious complications happened only in a small percentage of the patients as follows: cardiogenic shock 2.3%), cardiac arrest (6.3%), and cardiac death (1.1%) [.3%, cardFailure to recognize KS contributes to its underdiagnosis. Physicians should pay close attention to signs and symptoms of allergic reaction preceding the acute cardiac event and should consider KS in the differential diagnosis. KS has overall good prognosis and outcome; therefore, a multidisciplinary team from cardiology and allergy/immunology is recommended for the management of KS and post-hospital discharge follow-up.


Imatinib, one of the most used therapeutic agents to treat leukemia, is an inhibitor that specifically blocks the activity of tyrosine kinases. The molecule of imatinib is flexible and contains several functional groups able to take part in H-bonding and hydrophobic interactions. Analysis of molecular conformations for this drug was carried out using density functional theory calculations of rotation potentials along single bonds and by analyzing crystal structures of imatinib-containing compounds taken from the Cambridge Structural Database and the Protein Data Bank. Rotation along the N-C bond in the region of the amide group was found to be the reason for two relatively stable molecular conformations, an extended and a folded one. The role of various types of intermolecular interactions in stabilization of the particular molecular conformation was studied in terms of (i) the likelihood of H-bond formation, and (ii) their contribution to the Voronoi molecular surface. It is shown that experimentally observed hydrogen bonds are in accord with the likelihood of their formation. The number of H-bonds in ligand-receptor complexes surpasses that in imatinib salts due to the large number of donors and acceptors of H-bonding within the binding pocket of tyrosine kinases. Contribution of hydrophilic intermolecular interactions to the Voronoi molecular surface is similar for both conformations, while π...π stacking is more typical for the folded conformation of imatinib. Gleevec, Chronic myelogenic leukemia (CML) is caused by expression of a single oncoprotein resulting from the fusion of proteins involved in multiple signaling pathways . The fusSince 2012, a number of other crystal structures were additionally reported. Among them are crystal structures of two polymorphs of imatinib mesylate, that is the active pharmaceutical ingredient (API) of the therapeutic agent against CML, where the imatinib molecule adopted different conformations. However, correlations between various crystalline environments, intermolecular interactions, and imatinib conformations have not been studied before. Analysis of correlations would allow one to reveal the most abundant intermolecular interactions that tend to appear in all crystal structures regardless of molecular conformation. Another task of this comparison is to estimate the effect of a crystalline environment and molecular conformations on intermolecular interactions’ appearance. Similar types of interactions are present in both small-crystal structures and proteins  can be constructed of Voronoi polyhedra of all atoms the molecule consists of . The molHerein we report analysis of molecular flexibility using Density Functional Theory (DFT) calculations of rotation potentials for pure imatinib and its protonated forms, and comparison of intermolecular interactions of imatinib in different conformations and crystalline environment. H-bonds in salts and ligand-receptor complexes are compared. Contribution of various types of intermolecular interactions to the molecular surface of imatinib using the MVP approach is studied, and applicability of MVP-based analysis of intermolecular interactions to flexible molecules is demonstrated.In Values of Q1–Q8 torsion angles that describe rotation of functional groups and rings along single bonds are listed in + molecules were obtained from quantum chemical calculations at the B3LYP/6-31G(d) level of theory (see Ar (Q4) and along the C(pyridyl)-C(pyrimidine) bonds is characterized by the lowest rotation potential, followed by the potentials of rotation along C-CH2 bonds with pipyridine. The barriers of rotation along N–C bonds are higher except for the N(amide)-CAr bond. Experimentally observed geometry in general follows the calculations giving a variety of molecular conformations, mainly due to disposition of pipyridine fragment and rotation along the N(amide)-CAr bond . The rotation potentials for Ima and HImaCAr bond . ExperimTo sum up, imatinib belongs to flexible molecules with low barriers of rotation along the amide and methylene groups. The particular conformation depends on the interplay of inter- and intramolecular interactions affected by the crystalline environment. However, none of the studied compounds realizes strong intramolecular bonding, and all functional groups of the API remain available for intermolecular bonding only. Among all intermolecular interactions, competition of functional groups in the crystalline environment to form the strongest of these, the hydrogen bonds, can be numerically characterized by calculation of the likelihood of H-bond formation . The rol+ contains an additional donor of H-bond (tertiary ammonium), and counterions that also contain functional groups. However, H-bonding interactions in ligand–receptor complexes can be roughly estimated using functional groups of HIma+ and water molecules, as receptors are also to use amide groups to form hydrogen bonds with the API . Area under ROC curve of 0.79 indicates acceptable discrimination for the logistic model. The results of calculations indicate that, in general, water molecules and tertiary ammonium of piperidinium are better donors of H-bonding than secondary amine and amide groups. However, the difference between propensity of H-bond formation with water or pyridine, amide or pyrimidine as acceptors is rather low, which explains the absence of hydrates among salts, as it was analyzed in ref.  Å3 and  Å2. Thus, all molecular volumes and areas can be considered as coincident, and the role of various intermolecular interactions in stabilization of a molecular conformation can be estimated using one-way analysis of variance of their partial contributions to the total area of MVP.MVP of 21 independent HImahericity , indicate chains  or missip = 0.95 is equal to %, and only two crystal structures, namely, {RAYQEP} and {DUNTIQ} both containing 2,4,6-trinitrophenolate anion, do not fit within the confidence interval either at p = 0.95, or at p = 0.99 and 0.999. This may be related with the inclination of nitro groups to take part in O…H bonding, or the low number of hydrogen atoms in the 2,4,6-trinitrophenolate anion.For all molecules under discussion, hydrophobic H…H, C…H, C…C, and C…N and hydrophilic O…H and N…H interactions were found. Besides, all compounds taken from the Protein Data Bank realize S…H, C…O, and O…O interactions. Depending on chemical composition of a complex or salt, C…S, N…S, N…O, N…N, and Cl…H interactions can also appear. Thus, one can evaluate either the role of hydrophilic/hydrophobic interactions or of a particular interaction type found in all compounds using the Voronoi approach. Unexpectedly, despite variation in the chemical environment of the imatinib molecule in complexes and salts, c.a. ¾ of the molecular area goes to hydrophobic interactions. Their partial contribution varies in a narrow range and is equal to 75.8(1.5)%. Confidence interval at 2 for the hydrophobic interactions exceeds 70% (2 = 0.98). Absolute values of the area that goes to C…C and C…N interactions are rather low, 5.9  Å2 for the extended conformation and 29.3  Å2 for the folded conformation, or 1 and 4% of the mean molecular area, however, one should take into account that the Voronoi partitioning underestimates the contribution of π…π interactions to the total energy of crystal packing and to the molecular surface  Å3 and  Å2.Constancy of volume and total area of the molecular Voronoi polyhedron of imatinib in different crystalline environments and in various conformations was demonstrated. Their mean values were equal to 676.7(511) Å(iii)For all compounds except two picrates, 75.8(15)% of the total molecular area goes to hydrophobic interactions. Although the total number of strong hydrogen bonds of the imatinib molecule in the extended conformation is higher than that of the molecule in the folded conformation, the molecular area that goes to all hydrophobic interactions, or to all O…H and N…H, or to strong hydrogen bonds for both conformations is nearly the same. At the same time, contribution of π…π stacking interactions to the molecular area of imatinib molecules in the folded conformation is more prominent than to the area of molecules in the extended conformation.Flexibility of the imatinib molecule was numerically characterized using DFT calculations; for both Ima and HIma(iv)H-bond propensities tool can be applied for prediction of the most likely hydrogen bonds not only in crystals of small molecules, but also in ligand–receptor complexes.(v)Molecular Voronoi polyhedra were for the first time applied for analysis of variance of contribution of intermolecular interactions to the total molecular area depending on some molecular conformation. Strength and shortcomings of this approach were discussed.Methodological aspects of our work can be summarized as: